Beide Seiten der vorigen RevisionVorhergehende ÜberarbeitungNächste Überarbeitung | Vorhergehende Überarbeitung |
p:ki:fische4 [2024/03/31 19:13] – Ralf Kretzschmar | p:ki:fische4 [2025/08/27 10:43] (aktuell) – Tscherter Vincent |
---|
Navigation: [[:p:ki:fische1|🐟 Teil 1]] - [[:p:ki:fische2|🐟 Teil 2]] - [[:p:ki:fische3|🐟 Teil 3]] - [[:p:ki:fische4|🐟 Teil 4]] {{gem/mgr}}{{ gem/pageinfo}} | Navigation: [[:p:ki:fische1|🐟 Teil 1]] - [[:p:ki:fische2|🐟 Teil 2]] - [[:p:ki:fische3|🐟 Teil 3]] - [[:p:ki:fische4|🐟 Teil 4]] - [[:p:ki:fische_ki|🐟 Zusatzkapitel]] {{gem/mgr}}{{ gem/pageinfo}} |
| |
====== 🐟 Künstliche Intelligenz für echte Fische 4 ====== | ====== 🐟 Künstliche Intelligenz für echte Fische 4 ====== |
🎯 In dieser Reihe erfährst du, wie eine künstliche Intelligenz automatisiert Daten auswertet und beurteilt. Dazu begibst du dich auf raue See. | 🎯 In dieser Reihe erfährst du, wie eine künstliche Intelligenz automatisiert Daten auswertet und beurteilt. Dazu begibst du dich auf raue See. |
| |
| \\ |
~~INTOC~~ | ~~INTOC~~ |
| |
===== -#1 Was bisher geschah... ===== | ===== -#1 Was bisher geschah... ===== |
| |
👩🦰 Du hilfst Sigrún beim Bau eines Fischsortierapparats der Hering von Lodde unterscheiden kann. Als Herzstück hast du dafür ein neuronalen Netzes trainiert. Das Neuronale Netz erkennt rund 90% der Fische richtig, jedoch ist das immer noch zu schlecht um Sigrún die Arbeit abnehmen zu können. | 👩🦰 Du hilfst Sigrún beim Bau eines Fischsortierapparats der Hering von Lodde unterscheiden kann. Als Herzstück hast du dafür ein neuronalen Netzes trainiert. Das Neuronale Netz erkennt rund 90% der Fische richtig, jedoch ist das immer noch zu schlecht, um Sigrún die Arbeit abnehmen zu können. |
| |
😢 Musst du aufgeben? | 😢 Musst du aufgeben? |
| |
\\ | \\ |
[{{ p:pasted:classoverlap.png?185px|Überlappende Klassen((eigene Darstellung, [[https://creativecommons.org/publicdomain/zero/1.0/deed.de|CC0 1.0]])) }}] | <figure right>{{p:pasted:classoverlap.png?185px}}<caption>Überlappende Klassen((eigene Darstellung, [[https://creativecommons.org/publicdomain/zero/1.0/deed.de|CC0 1.0]])) </caption></figure> |
===== - Das Problem der überlappenden Klassen ===== | ===== - Das Problem der überlappenden Klassen ===== |
| |
- Starte mehrfach das Programm. Das Ziel ist es, möglichst wenige Fische zu verwerfen, aber gleichzeitig die anderen Fische zu 100 % korrekt zu trennen. Der Prozentwert bei ''🗑️'' gibt dir an, welcher Anteil der Fische verworfen wird. Der Prozentwert bei ''✔️'' gibt dir an, wie viele der anderen Fische korrekt klassifiziert werden. | - Starte mehrfach das Programm. Das Ziel ist es, möglichst wenige Fische zu verwerfen, aber gleichzeitig die anderen Fische zu 100 % korrekt zu trennen. Der Prozentwert bei ''🗑️'' gibt dir an, welcher Anteil der Fische verworfen wird. Der Prozentwert bei ''✔️'' gibt dir an, wie viele der anderen Fische korrekt klassifiziert werden. |
- Spiele mit den Parametern ''LERNRATE'', ''ANZAHL_HIDDEN_NEURONS'', ''ANZAHL_EPOCHEN'' und dem ''THRESHOLD''. Trage dein bestes Ergebnis (%-verworfen bei 100 % korrekt) in das nachfolgende Textfeld ein. Was bedeutet dein Ergebnis für Sigrún? {{gem/plain?0=N4XyA#4029d46d442013a7}} | - Spiele mit den Parametern ''LERNRATE'', ''ANZAHL_HIDDEN_NEURONS'', ''ANZAHL_EPOCHEN'' und dem ''THRESHOLD''. Trage dein bestes Ergebnis (%-verworfen bei 100 % korrekt) in das nachfolgende Textfeld ein. Was bedeutet dein Ergebnis für Sigrún? {{gem/plain?0=N4XyA#4029d46d442013a7}} |
{{exorciser/jspg?javascript=%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%0A%2F%2F%20Diese%20Trainings-%20und%20Updateparameter%20d%C3%BCrfen%20ge%C3%A4ndert%20werden.%0Aconst%20LERNRATE%20%3D%201%3B%20%2F%2F%20Dezimalzahl%20%3E%200%0Aconst%20ANZAHL_HIDDEN_NEURONS%20%3D%203%3B%20%2F%2F%20ganzzahliger%20Wert%20%3E%200%0Aconst%20ANZAHL_EPOCHEN%20%3D%202000%3B%20%2F%2F%20ganzzahliger%20Wert%20%3E%200%0Aconst%20EPOCHEN_FUER_GRAFIK_UPDATE%20%3D%20100%3B%20%2F%2F%20ganzzahlig%20Wert%20%3E%200%0Aconst%20THRESHOLD%20%3D%200.3%3B%20%2F%2F%20Dezimalzahl%20%3E%200%0A%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%0A%0A%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%2F%2F%20CONSTANTS%20AND%20GLOBAL%20VARIABLES%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%0A%0A%2F%2F%20constants%0Aconst%20DATA_RANGE%20%3D%2010%3B%0Aconst%20DATA_WINDOW_SIZE%20%3D%20200%3B%0Aconst%20DATA_SCALE%20%3D%20Math.round%28DATA_WINDOW_SIZE%20%2F%20DATA_RANGE%29%3B%0Aconst%20NUM_DATA_PIXEL%20%3D%2050%3B%0Aconst%20PIXEL_SIZE%20%3D%20Math.round%28DATA_WINDOW_SIZE%20%2F%20NUM_DATA_PIXEL%29%3B%0A%0A%2F%2F%20training%20data%0Aconst%20trainInputArray%20%3D%20%5B%0A%09%5B2.5%2C%206.0%5D%2C%0A%09%5B3.5%2C%201.5%5D%2C%0A%09%5B3.5%2C%204.0%5D%2C%0A%09%5B4.0%2C%206.0%5D%2C%0A%09%5B4.0%2C%207.0%5D%2C%0A%09%5B4.5%2C%203.0%5D%2C%0A%09%5B5.0%2C%205.0%5D%2C%0A%09%5B5.5%2C%206.0%5D%2C%0A%09%5B6.5%2C%203.0%5D%2C%0A%09%5B7.0%2C%205.5%5D%2C%0A%09%5B7.5%2C%204.0%5D%2C%0A%09%5B8.5%2C%205.5%5D%2C%0A%09%5B1.5%2C%203.0%5D%2C%0A%09%5B1.5%2C%204.5%5D%2C%0A%09%5B1.5%2C%207.0%5D%2C%0A%09%5B2.0%2C%201.5%5D%2C%0A%09%5B3.0%2C%203.0%5D%2C%0A%09%5B3.0%2C%205.5%5D%2C%0A%09%5B3.0%2C%206.5%5D%2C%0A%09%5B4.0%2C%208.5%5D%2C%0A%09%5B4.5%2C%206.5%5D%2C%0A%09%5B6.5%2C%207.5%5D%2C%0A%09%5B8.0%2C%206.5%5D%2C%0A%09%5B8.0%2C%208.5%5D%0A%5D%3B%0Aconst%20trainOutputArray%20%3D%20%5B0%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%5D%3B%0Aconst%20trainInputMax%20%3D%20%5B9.0%2C%208.5%5D%3B%0Aconst%20trainInputMin%20%3D%20%5B1.5%2C%201.5%5D%3B%0A%0A%2F%2F%20validation%20data%0Aconst%20validInputArray%20%3D%20%5B%0A%09%5B2.5%2C%207.0%5D%2C%0A%09%5B3.5%2C%201.0%5D%2C%0A%09%5B3.5%2C%207.0%5D%2C%0A%09%5B4.0%2C%203.5%5D%2C%0A%09%5B4.5%2C%206.5%5D%2C%0A%09%5B4.5%2C%202.5%5D%2C%0A%09%5B4.5%2C%205.0%5D%2C%0A%09%5B6.0%2C%202.5%5D%2C%0A%09%5B6.0%2C%204.5%5D%2C%0A%09%5B6.5%2C%205.5%5D%2C%0A%09%5B7.5%2C%204.5%5D%2C%0A%09%5B8.5%2C%205.0%5D%2C%0A%09%5B1.5%2C%205.0%5D%2C%0A%09%5B1.5%2C%206.5%5D%2C%0A%09%5B2.0%2C%201.5%5D%2C%0A%09%5B2.5%2C%203.5%5D%2C%0A%09%5B2.5%2C%206.0%5D%2C%0A%09%5B3.5%2C%206.0%5D%2C%0A%09%5B4.0%2C%208.0%5D%2C%0A%09%5B4.0%2C%207.0%5D%2C%0A%09%5B5.5%2C%208.5%5D%2C%0A%09%5B6.5%2C%207.0%5D%2C%0A%09%5B7.5%2C%208.5%5D%2C%0A%09%5B8.5%2C%207.0%5D%0A%5D%3B%0Aconst%20validOutputArray%20%3D%20%5B0%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%5D%3B%0A%0A%2F%2F%20global%20variables%0Alet%20model%2C%20trainInput%2C%20trainOutput%2C%20validInput%2C%20validOutput%2C%20testInput%2C%20actualEpoch%2C%20actualLogs%2C%20trainBuffer%2C%20validBuffer%2C%20decisionBuffer%3B%0A%0A%0A%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%2F%2F%20NEURAL%20NETWORK%20FUNCTIONS%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%0A%0A%2F%2F%0A%2F%2F%20generate%20data%20tensors%0A%2F%2F%0Afunction%20generateTensors%28%29%20%7B%0A%09let%20normalizedTrainInputArray%20%3D%20%5B%5D%3B%0A%09let%20normalizedValidInputArray%20%3D%20%5B%5D%3B%0A%09let%20normalizedTestInputArray%20%3D%20%5B%5D%3B%0A%0A%09%2F%2F%20normalize%20training%20and%20validation%20inputs%0A%09for%20%28i%20%3D%200%3B%20i%20%3C%20trainInputArray.length%3B%20i%2B%2B%29%20%7B%0A%09%09normalizedTrainInputArray.push%28%5B%28trainInputArray%5Bi%5D%5B0%5D%20-%20trainInputMin%5B0%5D%29%20%2F%20%28trainInputMax%5B0%5D%20-%20trainInputMin%5B0%5D%29%2C%20%28trainInputArray%5Bi%5D%5B1%5D%20-%20trainInputMin%5B1%5D%29%20%2F%20%28trainInputMax%5B1%5D%20-%20trainInputMin%5B1%5D%29%5D%29%3B%0A%09%09normalizedValidInputArray.push%28%5B%28validInputArray%5Bi%5D%5B0%5D%20-%20trainInputMin%5B0%5D%29%20%2F%20%28trainInputMax%5B0%5D%20-%20trainInputMin%5B0%5D%29%2C%20%28validInputArray%5Bi%5D%5B1%5D%20-%20trainInputMin%5B1%5D%29%20%2F%20%28trainInputMax%5B1%5D%20-%20trainInputMin%5B1%5D%29%5D%29%3B%0A%09%7D%0A%0A%09%2F%2F%20generate%20training%20input%20and%20output%20tensors%0A%09trainInput%20%3D%20tf.tensor2d%28normalizedTrainInputArray%2C%20%5BnormalizedTrainInputArray.length%2C%202%5D%29%3B%0A%09trainOutput%20%3D%20tf.tensor2d%28trainOutputArray%2C%20%5BtrainOutputArray.length%2C%201%5D%29%3B%0A%09%2F%2F%20let%20trainOutput%20%3D%20tf.oneHot%28tf.tensor1d%28trainOutputArray%29.toInt%28%29%2C%202%29%3B%0A%09%2F%2F%20trainInput.print%28%29%3B%20%2F%2F%20Print%20Tensor%0A%0A%09%2F%2F%20generate%20validation%20input%20and%20output%20tensors%0A%09validInput%20%3D%20tf.tensor2d%28normalizedValidInputArray%2C%20%5BnormalizedValidInputArray.length%2C%202%5D%29%3B%0A%09validOutput%20%3D%20tf.tensor2d%28validOutputArray%2C%20%5BvalidOutputArray.length%2C%201%5D%29%3B%0A%09%2F%2F%20let%20validOutput%20%3D%20tf.oneHot%28tf.tensor1d%28validOutputArray%29.toInt%28%29%2C%202%29%3B%0A%0A%09%2F%2F%20calculate%20normalized%20testing%20inputs%20for%20visualisation%0A%09for%20%28i%20%3D%200%3B%20i%20%3C%20NUM_DATA_PIXEL%20%2B%201%3B%20i%20%3D%20i%20%2B%201%29%20%7B%0A%09%09for%20%28j%20%3D%200%3B%20j%20%3C%20NUM_DATA_PIXEL%20%2B%201%3B%20j%20%3D%20j%20%2B%201%29%20%7B%0A%09%09%09normalizedTestInputArray.push%28%5B%28i%20%2F%20NUM_DATA_PIXEL%20%2a%20DATA_RANGE%20-%20trainInputMin%5B0%5D%29%20%2F%20%28trainInputMax%5B0%5D%20-%20trainInputMin%5B0%5D%29%2C%20%28j%20%2F%20NUM_DATA_PIXEL%20%2a%20DATA_RANGE%20-%20trainInputMin%5B1%5D%29%20%2F%20%28trainInputMax%5B1%5D%20-%20trainInputMin%5B1%5D%29%5D%29%3B%0A%09%09%7D%0A%09%7D%0A%0A%09%2F%2F%20generate%20testing%20input%20tensor%20for%20visualisation%0A%09testInput%20%3D%20tf.tensor2d%28normalizedTestInputArray%2C%20%5BnormalizedTestInputArray.length%2C%202%5D%29%3B%0A%09%2F%2F%09testInput.print%28%29%3B%0A%7D%0A%0A%0A%2F%2F%0A%2F%2F%20build%20neural%20network%20model%20and%20define%20training%0A%2F%2F%0Afunction%20compileModel%28%29%20%7B%0A%09%2F%2F%20neural%20network%20structure%0A%09model%20%3D%20tf.sequential%28%7B%0A%09%09layers%3A%20%5B%0A%09%09%09tf.layers.dense%28%7B%0A%09%09%09%09name%3A%20%27HiddenLayer1%27%2C%0A%09%09%09%09inputShape%3A%20%5B2%5D%2C%0A%09%09%09%09units%3A%20ANZAHL_HIDDEN_NEURONS%2C%0A%09%09%09%09activation%3A%20%27tanh%27%0A%09%09%09%7D%29%2C%0A%09%09%09tf.layers.dense%28%7B%0A%09%09%09%09name%3A%20%27OutputLayer%27%2C%0A%09%09%09%09units%3A%201%2C%0A%09%09%09%09activation%3A%20%27sigmoid%27%0A%09%09%09%7D%29%0A%09%09%5D%0A%09%7D%29%3B%0A%0A%09%2F%2F%20neural%20network%20training%0A%09model.compile%28%7B%0A%09%09optimizer%3A%20tf.train.sgd%28LERNRATE%29%2C%0A%09%09loss%3A%20tf.losses.meanSquaredError%2C%0A%09%09metrics%3A%20%5B%27mse%27%5D%2C%0A%09%7D%29%3B%0A%7D%0A%0A%0A%2F%2F%0A%2F%2F%20train%20neural%20network%0A%2F%2F%0Aasync%20function%20trainModel%28%29%20%7B%0A%09await%20model.fit%28%0A%09%09trainInput%2C%20trainOutput%2C%20%7B%0A%09%09%09epochs%3A%20ANZAHL_EPOCHEN%2C%0A%09%09%09shuffle%3A%20true%2C%0A%09%09%09callbacks%3A%20%5B%7B%0A%09%09%09%09onEpochEnd%3A%20async%28epoch%2C%20logs%29%20%3D%3E%20%7B%0A%09%09%09%09%09%2F%2F%20remember%20epoch%20number%20if%20interrupted%0A%09%09%09%09%09actualEpoch%20%3D%20epoch%20%2B%201%3B%0A%09%09%09%09%09actualLogs%20%3D%20logs%3B%0A%09%09%09%09%09%2F%2F%20initiate%20graphic%20update%0A%09%09%09%09%09if%20%28%28%28actualEpoch%29%20%25%20EPOCHEN_FUER_GRAFIK_UPDATE%20%3D%3D%3D%200%29%20%7C%7C%20%28epoch%20%3D%3D%3D%200%29%29%20%7B%0A%09%09%09%09%09%09drawPrediction%28actualEpoch%2C%20logs.loss%29%3B%0A%09%09%09%09%09%7D%0A%09%09%09%09%7D%0A%09%09%09%7D%2C%20%5D%0A%09%09%7D%0A%09%29%3B%0A%7D%0A%0A%0A%2F%2F%0A%2F%2F%20calculate%20percentage%20of%20correct%20classifications%0A%2F%2F%0Afunction%20calculatePercentageCorrect%28predictedOutput%2C%20trueOutput%29%20%7B%0A%09let%20correct%20%3D%200%3B%0A%09let%20rejected%20%3D%200%3B%0A%09for%20%28i%20%3D%200%3B%20i%20%3C%20predictedOutput.length%3B%20i%2B%2B%29%20%7B%0A%09%09if%20%28predictedOutput%5Bi%5D%20%3C%20%281%20-%20THRESHOLD%29%20%26%26%20predictedOutput%5Bi%5D%20%3E%20THRESHOLD%29%20%7B%0A%09%09%09rejected%20%3D%20rejected%20%2B%201%3B%0A%09%09%7D%20else%20%7B%0A%09%09%09if%20%28%28trueOutput%5Bi%5D%20%3D%3D%3D%201%20%26%26%20predictedOutput%5Bi%5D%20%3E%3D%200.5%29%20%7C%7C%20%28trueOutput%5Bi%5D%20%3D%3D%3D%200%20%26%26%20predictedOutput%5Bi%5D%20%3C%200.5%29%29%20%7B%0A%09%09%09%09correct%20%3D%20correct%20%2B%201%3B%0A%09%09%09%7D%0A%09%09%7D%0A%09%7D%0A%09return%20%7B%0A%09%09correct%3A%20Math.round%28correct%20%2F%20%28predictedOutput.length%20-%20rejected%29%20%2a%20100%29%2C%0A%09%09rejected%3A%20Math.round%28rejected%20%2F%20predictedOutput.length%20%2a%20100%29%0A%09%7D%3B%0A%7D%0A%0A%0A%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%2F%2F%20FUNCTIONS%20FOR%20VISUALISATION%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%0A%0A%2F%2F%0A%2F%2F%20decision%20boundary%20and%20network%20output%0A%2F%2F%0Afunction%20drawPrediction%28epoch%2C%20mseTrain%29%20%7B%0A%09%2F%2F%20make%20predictions%20with%20neural%20network%0A%09let%20training%20%3D%20model.predict%28trainInput%29.arraySync%28%29%3B%0A%09let%20validation%20%3D%20model.predict%28validInput%29.arraySync%28%29%3B%0A%09let%20prediction%20%3D%20model.predict%28testInput%29.arraySync%28%29%3B%0A%0A%09%2F%2F%20calculate%20mse%20and%20percentages%20of%20correct%20classifications%0A%09let%20trainCorrect%20%3D%20calculatePercentageCorrect%28training%2C%20trainOutputArray%29%3B%0A%09let%20validCorrect%20%3D%20calculatePercentageCorrect%28validation%2C%20validOutputArray%29%3B%0A%0A%09%2F%2F%20decision%20boundary%20and%20input%20feature%20space%0A%09decisionBuffer.noStroke%28%29%3B%0A%09let%20element%20%3D%200%3B%0A%09for%20%28i%20%3D%200%3B%20i%20%3C%20NUM_DATA_PIXEL%20%2B%201%3B%20i%20%3D%20i%20%2B%201%29%20%7B%0A%09%09for%20%28j%20%3D%200%3B%20j%20%3C%20NUM_DATA_PIXEL%20%2B%201%3B%20j%20%3D%20j%20%2B%201%29%20%7B%0A%09%09%09%2F%2F%20transform%20neural%20network%20output%20into%20a%20color%0A%09%09%09if%20%28prediction%5Belement%5D%5B0%5D%20%3C%20%281%20-%20THRESHOLD%29%20%26%26%20prediction%5Belement%5D%5B0%5D%20%3E%20THRESHOLD%29%20%7B%0A%09%09%09%09decisionBuffer.fill%28%22white%22%29%3B%0A%09%09%09%7D%20else%20%7B%0A%09%09%09%09if%20%28prediction%5Belement%5D%5B0%5D%20%3E%200.5%29%20%7B%0A%09%09%09%09%09decisionBuffer.fill%28%22lightgreen%22%29%3B%0A%09%09%09%09%7D%20else%20%7B%0A%09%09%09%09%09decisionBuffer.fill%28%22lightblue%22%29%3B%0A%09%09%09%09%7D%0A%09%09%09%7D%0A%09%09%09%2F%2F%20check%20for%20decision%20boundary%20and%20alter%20color%0A%09%09%09if%20%28%28element%20%25%20%28NUM_DATA_PIXEL%20%2B%201%29%29%20%21%3D%3D%200%20%26%26%20%28%28prediction%5Belement%5D%5B0%5D%20%3E%200.5%20%26%26%20prediction%5Belement%20-%201%5D%5B0%5D%20%3C%3D%200.5%29%20%7C%7C%20%28prediction%5Belement%5D%5B0%5D%20%3C%3D%200.5%20%26%26%20prediction%5Belement%20-%201%5D%5B0%5D%20%3E%200.5%29%29%29%20%7B%0A%09%09%09%09decisionBuffer.fill%28%27red%27%29%3B%0A%09%09%09%7D%0A%09%09%09if%20%28element%20%3E%3D%20NUM_DATA_PIXEL%20%2B%201%20%26%26%20%28%28prediction%5Belement%5D%5B0%5D%20%3E%200.5%20%26%26%20prediction%5Belement%20-%20%28NUM_DATA_PIXEL%20%2B%201%29%5D%5B0%5D%20%3C%3D%200.5%29%20%7C%7C%20%28prediction%5Belement%5D%5B0%5D%20%3C%3D%200.5%20%26%26%20prediction%5Belement%20-%20%28NUM_DATA_PIXEL%20%2B%201%29%5D%5B0%5D%20%3E%200.5%29%29%29%20%7B%0A%09%09%09%09decisionBuffer.fill%28%27red%27%29%3B%0A%09%09%09%7D%0A%09%09%09decisionBuffer.rect%28DATA_SCALE%20%2a%20i%20%2F%20NUM_DATA_PIXEL%20%2a%20DATA_RANGE%20-%20PIXEL_SIZE%20%2F%202%2C%20DATA_SCALE%20%2a%20%2810%20-%20j%20%2F%20NUM_DATA_PIXEL%20%2a%20DATA_RANGE%29%20-%20PIXEL_SIZE%20%2F%202%2C%20PIXEL_SIZE%2C%20PIXEL_SIZE%29%3B%0A%09%09%09element%20%3D%20element%20%2B%201%3B%0A%09%09%7D%0A%09%7D%0A%09image%28decisionBuffer%2C%200%2C%200%29%3B%0A%09image%28decisionBuffer%2C%20DATA_WINDOW_SIZE%2C%200%29%3B%0A%0A%09%2F%2F%20draw%20training%20and%20validation%20samples%0A%09image%28trainBuffer%2C%200%2C%200%29%3B%0A%09image%28validBuffer%2C%20DATA_WINDOW_SIZE%2C%200%29%3B%0A%0A%09%2F%2F%20add%20lables%20to%20training%20and%20validation%20feature%20space%0A%09noStroke%28%29%3B%0A%09text%28%22Training%3A%20%22%20%2B%20trainCorrect.correct%20%2B%20%22%25%20%E2%9C%94%EF%B8%8F%EF%B8%8F%2C%20%22%20%2B%20trainCorrect.rejected%20%2B%20%22%25%20%F0%9F%97%91%22%2C%202%20%2a%20PIXEL_SIZE%2C%204%20%2a%20PIXEL_SIZE%29%3B%0A%09text%28%22Validation%3A%20%22%20%2B%20validCorrect.correct%20%2B%20%22%25%20%E2%9C%94%EF%B8%8F%2C%20%22%20%2B%20validCorrect.rejected%20%2B%20%22%25%20%F0%9F%97%91%22%2C%20DATA_WINDOW_SIZE%20%2B%202%20%2a%20PIXEL_SIZE%2C%204%20%2a%20PIXEL_SIZE%29%3B%0A%0A%09%2F%2F%20print%20training%20and%20validation%20results%20to%20console%0A%09console.log%28%22%7C%7C%20%22%20%2B%20epoch.toString%28%29.padStart%286%2C%20%22%20%22%29%20%2B%20%22%20%7C%7C%20%22%20%2B%20trainCorrect.correct.toString%28%29.padStart%286%2C%20%22%20%22%29%20%2B%20%22%25%20%7C%20%22%20%2B%20trainCorrect.rejected.toString%28%29.padStart%287%2C%20%22%20%22%29%20%2B%20%22%25%20%7C%7C%20%22%20%2B%20validCorrect.correct.toString%28%29.padStart%286%2C%20%22%20%22%29%20%2B%20%22%25%20%7C%20%22%20%2B%20validCorrect.rejected.toString%28%29.padStart%287%2C%20%22%20%22%29%20%2B%20%22%25%20%7C%7C%22%29%3B%0A%7D%0A%0A%0A%2F%2F%0A%2F%2F%20draw%20data%20in%20graphic%20buffer%0A%2F%2F%0Afunction%20drawDataInBuffer%28inputData%2C%20outputData%2C%20buffer%29%20%7B%0A%09buffer.noFill%28%29%3B%0A%09buffer.strokeWeight%28PIXEL_SIZE%20%2F%202%29%3B%0A%09buffer.rect%280%2C%200%2C%20DATA_WINDOW_SIZE%2C%20DATA_WINDOW_SIZE%29%3B%0A%09for%20%28i%20%3D%200%3B%20i%20%3C%20inputData.length%3B%20i%2B%2B%29%20%7B%0A%09%09if%20%28outputData%5Bi%5D%20%3D%3D%3D%201%29%20%7B%0A%09%09%09%2F%2F%20green%20circle%20for%20output%20lable%20%3D%3D%3D%201%0A%09%09%09buffer.stroke%28%22darkgreen%22%29%3B%0A%09%09%09buffer.circle%28DATA_SCALE%20%2a%20inputData%5Bi%5D%5B0%5D%2C%20DATA_SCALE%20%2a%20%2810%20-%20inputData%5Bi%5D%5B1%5D%29%2C%202%20%2a%20PIXEL_SIZE%29%3B%0A%09%09%7D%20else%20%7B%0A%09%09%09%2F%2F%20blue%20cross%20for%20output%20lable%20%3D%3D%3D%200%0A%09%09%09buffer.stroke%28%22blue%22%29%3B%0A%09%09%09buffer.line%28DATA_SCALE%20%2a%20inputData%5Bi%5D%5B0%5D%20%2B%20PIXEL_SIZE%2C%20DATA_SCALE%20%2a%20%2810%20-%20inputData%5Bi%5D%5B1%5D%29%20%2B%20PIXEL_SIZE%2C%20DATA_SCALE%20%2a%20inputData%5Bi%5D%5B0%5D%20-%20PIXEL_SIZE%2C%20DATA_SCALE%20%2a%20%2810%20-%20inputData%5Bi%5D%5B1%5D%29%20-%20PIXEL_SIZE%29%3B%0A%09%09%09buffer.line%28DATA_SCALE%20%2a%20inputData%5Bi%5D%5B0%5D%20%2B%20PIXEL_SIZE%2C%20DATA_SCALE%20%2a%20%2810%20-%20inputData%5Bi%5D%5B1%5D%29%20-%20PIXEL_SIZE%2C%20DATA_SCALE%20%2a%20inputData%5Bi%5D%5B0%5D%20-%20PIXEL_SIZE%2C%20DATA_SCALE%20%2a%20%2810%20-%20inputData%5Bi%5D%5B1%5D%29%20%2B%20PIXEL_SIZE%29%3B%0A%09%09%7D%0A%09%7D%0A%7D%0A%0A%0A%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%2F%2F%20MAIN%20PROGRAM%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%0A%0A%2F%2F%0A%2F%2F%20p5.js%20setup%28%29%0A%2F%2F%0Aasync%20function%20setup%28%29%20%7B%20%2F%2Fnoprotect%20%28for%20large%20arrays%29%0A%09%2F%2F%20initiate%20console%20output%0A%09console.log%28%22%7C%7C%20%20%20%20%20%20%20%20%7C%7C%20%20%20%20%20%20Training%20%20%20%20%20%20%7C%7C%20%20%20%20%20Validation%20%20%20%20%20%7C%7C%22%29%3B%0A%09console.log%28%22%7C%7C%20Epoche%20%7C%7C%20korrekt%20%7C%20rejected%20%7C%7C%20korrekt%20%7C%20rejected%20%7C%7C%22%29%3B%0A%0A%09%2F%2F%20create%20canvas%0A%09createCanvas%282%20%2a%20DATA_WINDOW_SIZE%2C%20DATA_WINDOW_SIZE%29%3B%0A%09textSize%28PIXEL_SIZE%20%2a%203%29%3B%0A%0A%09%2F%2F%20create%20all%20grafic%20buffers%0A%09trainBuffer%20%3D%20createGraphics%28DATA_WINDOW_SIZE%2C%20DATA_WINDOW_SIZE%29%3B%0A%09validBuffer%20%3D%20createGraphics%28DATA_WINDOW_SIZE%2C%20DATA_WINDOW_SIZE%29%3B%0A%09decisionBuffer%20%3D%20createGraphics%28DATA_WINDOW_SIZE%2C%20DATA_WINDOW_SIZE%29%3B%0A%0A%09%2F%2F%20draw%20initial%20training%20and%20validation%20buffer%0A%09drawDataInBuffer%28trainInputArray%2C%20trainOutputArray%2C%20trainBuffer%29%3B%0A%09drawDataInBuffer%28validInputArray%2C%20validOutputArray%2C%20validBuffer%29%3B%0A%09image%28trainBuffer%2C%200%2C%200%29%3B%0A%09image%28validBuffer%2C%20DATA_WINDOW_SIZE%2C%200%29%3B%0A%0A%09%2F%2F%20data%20preprocessing%0A%09generateTensors%28%29%3B%0A%0A%09%2F%2F%20define%20model%20and%20training%0A%09compileModel%28%29%3B%0A%0A%09%2F%2F%20train%20and%20visualise%20neural%20network%0A%09await%20trainModel%28%29%3B%0A%0A%09%2F%2F%20end%20of%20training%0A%09console.log%28%22Das%20Training%20ist%20beendet%20%3A-%29%22%29%3B%0A%0A%7D%0A%0A%0A%2F%2F%0A%2F%2F%20p5.js%20keyPressed%28%29%20ESC%20%3D%20emergency%20stop%0A%2F%2F%0Afunction%20keyPressed%28%29%20%7B%0A%09if%20%28keyCode%20%3D%3D%3D%2027%29%20%7B%20%2F%2F%20ESC%20key%0A%09%09%2F%2F%20initiate%20stop%20of%20training%20after%20next%20epoch%0A%09%09model.stopTraining%20%3D%20true%3B%0A%09%09%2F%2F%20response%20to%20user%0A%09%09console.log%28%22Training%20wurde%20Abgebrochen%21%20Finales%20Resultat%3A%22%29%3B%0A%09%09%2F%2F%20draw%20final%20Prediction%0A%09%09drawPrediction%28actualEpoch%2C%20actualLogs.loss%29%3B%0A%09%7D%0A%7D&css=undefined&html=%3Cscript%20src%3D%22https%3A%2F%2Fcdn.jsdelivr.net%2Fnpm%2Fp5%22%3E%3C%2Fscript%3E%0A%3Cscript%20src%3D%22https%3A%2F%2Fcdn.jsdelivr.net%2Fnpm%2F%40tensorflow%2Ftfjs%40latest%2Fdist%2Ftf.min.js%22%3E%3C%2Fscript%3E&autorun=off&height=500px#OverlapDetection}} | {{exorciser/jspg?javascript=%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%0A%2F%2F%20Diese%20Trainings-%20und%20Updateparameter%20d%C3%BCrfen%20ge%C3%A4ndert%20werden.%0Aconst%20LERNRATE%20%3D%201%3B%20%2F%2F%20Dezimalzahl%20%3E%200%0Aconst%20ANZAHL_HIDDEN_NEURONS%20%3D%203%3B%20%2F%2F%20ganzzahliger%20Wert%20%3E%200%0Aconst%20ANZAHL_EPOCHEN%20%3D%202000%3B%20%2F%2F%20ganzzahliger%20Wert%20%3E%200%0Aconst%20EPOCHEN_FUER_GRAFIK_UPDATE%20%3D%20100%3B%20%2F%2F%20ganzzahlig%20Wert%20%3E%200%0Aconst%20THRESHOLD%20%3D%200.3%3B%20%2F%2F%20Dezimalzahl%20%3E%200%0A%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%0A%0A%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%2F%2F%20CONSTANTS%20AND%20GLOBAL%20VARIABLES%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%0A%0A%2F%2F%20constants%0Aconst%20DATA_RANGE%20%3D%2010%3B%0Aconst%20DATA_WINDOW_SIZE%20%3D%20200%3B%0Aconst%20DATA_SCALE%20%3D%20Math.round%28DATA_WINDOW_SIZE%20%2F%20DATA_RANGE%29%3B%0Aconst%20NUM_DATA_PIXEL%20%3D%2050%3B%0Aconst%20PIXEL_SIZE%20%3D%20Math.round%28DATA_WINDOW_SIZE%20%2F%20NUM_DATA_PIXEL%29%3B%0A%0A%2F%2F%20training%20data%0Aconst%20trainInputArray%20%3D%20%5B%0A%09%5B2.5%2C%206.0%5D%2C%0A%09%5B3.5%2C%201.5%5D%2C%0A%09%5B3.5%2C%204.0%5D%2C%0A%09%5B4.0%2C%206.0%5D%2C%0A%09%5B4.0%2C%207.0%5D%2C%0A%09%5B4.5%2C%203.0%5D%2C%0A%09%5B5.0%2C%205.0%5D%2C%0A%09%5B5.5%2C%206.0%5D%2C%0A%09%5B6.5%2C%203.0%5D%2C%0A%09%5B7.0%2C%205.5%5D%2C%0A%09%5B7.5%2C%204.0%5D%2C%0A%09%5B8.5%2C%205.5%5D%2C%0A%09%5B1.5%2C%203.0%5D%2C%0A%09%5B1.5%2C%204.5%5D%2C%0A%09%5B1.5%2C%207.0%5D%2C%0A%09%5B2.0%2C%201.5%5D%2C%0A%09%5B3.0%2C%203.0%5D%2C%0A%09%5B3.0%2C%205.5%5D%2C%0A%09%5B3.0%2C%206.5%5D%2C%0A%09%5B4.0%2C%208.5%5D%2C%0A%09%5B4.5%2C%206.5%5D%2C%0A%09%5B6.5%2C%207.5%5D%2C%0A%09%5B8.0%2C%206.5%5D%2C%0A%09%5B8.0%2C%208.5%5D%0A%5D%3B%0Aconst%20trainOutputArray%20%3D%20%5B0%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%5D%3B%0Aconst%20trainInputMax%20%3D%20%5B9.0%2C%208.5%5D%3B%0Aconst%20trainInputMin%20%3D%20%5B1.5%2C%201.5%5D%3B%0A%0A%2F%2F%20validation%20data%0Aconst%20validInputArray%20%3D%20%5B%0A%09%5B2.5%2C%207.0%5D%2C%0A%09%5B3.5%2C%201.0%5D%2C%0A%09%5B3.5%2C%207.0%5D%2C%0A%09%5B4.0%2C%203.5%5D%2C%0A%09%5B4.5%2C%206.5%5D%2C%0A%09%5B4.5%2C%202.5%5D%2C%0A%09%5B4.5%2C%205.0%5D%2C%0A%09%5B6.0%2C%202.5%5D%2C%0A%09%5B6.0%2C%204.5%5D%2C%0A%09%5B6.5%2C%205.5%5D%2C%0A%09%5B7.5%2C%204.5%5D%2C%0A%09%5B8.5%2C%205.0%5D%2C%0A%09%5B1.5%2C%205.0%5D%2C%0A%09%5B1.5%2C%206.5%5D%2C%0A%09%5B2.0%2C%201.5%5D%2C%0A%09%5B2.5%2C%203.5%5D%2C%0A%09%5B2.5%2C%206.0%5D%2C%0A%09%5B3.5%2C%206.0%5D%2C%0A%09%5B4.0%2C%208.0%5D%2C%0A%09%5B4.0%2C%207.0%5D%2C%0A%09%5B5.5%2C%208.5%5D%2C%0A%09%5B6.5%2C%207.0%5D%2C%0A%09%5B7.5%2C%208.5%5D%2C%0A%09%5B8.5%2C%207.0%5D%0A%5D%3B%0Aconst%20validOutputArray%20%3D%20%5B0%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%200%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%2C%201%5D%3B%0A%0A%2F%2F%20global%20variables%0Alet%20model%2C%20trainInput%2C%20trainOutput%2C%20validInput%2C%20validOutput%2C%20testInput%2C%20actualEpoch%2C%20actualLogs%2C%20trainBuffer%2C%20validBuffer%2C%20decisionBuffer%3B%0A%0A%0A%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%2F%2F%20NEURAL%20NETWORK%20FUNCTIONS%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%0A%0A%2F%2F%0A%2F%2F%20generate%20data%20tensors%0A%2F%2F%0Afunction%20generateTensors%28%29%20%7B%0A%09let%20normalizedTrainInputArray%20%3D%20%5B%5D%3B%0A%09let%20normalizedValidInputArray%20%3D%20%5B%5D%3B%0A%09let%20normalizedTestInputArray%20%3D%20%5B%5D%3B%0A%0A%09%2F%2F%20normalize%20training%20and%20validation%20inputs%0A%09for%20%28i%20%3D%200%3B%20i%20%3C%20trainInputArray.length%3B%20i%2B%2B%29%20%7B%0A%09%09normalizedTrainInputArray.push%28%5B%28trainInputArray%5Bi%5D%5B0%5D%20-%20trainInputMin%5B0%5D%29%20%2F%20%28trainInputMax%5B0%5D%20-%20trainInputMin%5B0%5D%29%2C%20%28trainInputArray%5Bi%5D%5B1%5D%20-%20trainInputMin%5B1%5D%29%20%2F%20%28trainInputMax%5B1%5D%20-%20trainInputMin%5B1%5D%29%5D%29%3B%0A%09%09normalizedValidInputArray.push%28%5B%28validInputArray%5Bi%5D%5B0%5D%20-%20trainInputMin%5B0%5D%29%20%2F%20%28trainInputMax%5B0%5D%20-%20trainInputMin%5B0%5D%29%2C%20%28validInputArray%5Bi%5D%5B1%5D%20-%20trainInputMin%5B1%5D%29%20%2F%20%28trainInputMax%5B1%5D%20-%20trainInputMin%5B1%5D%29%5D%29%3B%0A%09%7D%0A%0A%09%2F%2F%20generate%20training%20input%20and%20output%20tensors%0A%09trainInput%20%3D%20tf.tensor2d%28normalizedTrainInputArray%2C%20%5BnormalizedTrainInputArray.length%2C%202%5D%29%3B%0A%09trainOutput%20%3D%20tf.tensor2d%28trainOutputArray%2C%20%5BtrainOutputArray.length%2C%201%5D%29%3B%0A%09%2F%2F%20let%20trainOutput%20%3D%20tf.oneHot%28tf.tensor1d%28trainOutputArray%29.toInt%28%29%2C%202%29%3B%0A%09%2F%2F%20trainInput.print%28%29%3B%20%2F%2F%20Print%20Tensor%0A%0A%09%2F%2F%20generate%20validation%20input%20and%20output%20tensors%0A%09validInput%20%3D%20tf.tensor2d%28normalizedValidInputArray%2C%20%5BnormalizedValidInputArray.length%2C%202%5D%29%3B%0A%09validOutput%20%3D%20tf.tensor2d%28validOutputArray%2C%20%5BvalidOutputArray.length%2C%201%5D%29%3B%0A%09%2F%2F%20let%20validOutput%20%3D%20tf.oneHot%28tf.tensor1d%28validOutputArray%29.toInt%28%29%2C%202%29%3B%0A%0A%09%2F%2F%20calculate%20normalized%20testing%20inputs%20for%20visualisation%0A%09for%20%28i%20%3D%200%3B%20i%20%3C%20NUM_DATA_PIXEL%20%2B%201%3B%20i%20%3D%20i%20%2B%201%29%20%7B%0A%09%09for%20%28j%20%3D%200%3B%20j%20%3C%20NUM_DATA_PIXEL%20%2B%201%3B%20j%20%3D%20j%20%2B%201%29%20%7B%0A%09%09%09normalizedTestInputArray.push%28%5B%28i%20%2F%20NUM_DATA_PIXEL%20%2a%20DATA_RANGE%20-%20trainInputMin%5B0%5D%29%20%2F%20%28trainInputMax%5B0%5D%20-%20trainInputMin%5B0%5D%29%2C%20%28j%20%2F%20NUM_DATA_PIXEL%20%2a%20DATA_RANGE%20-%20trainInputMin%5B1%5D%29%20%2F%20%28trainInputMax%5B1%5D%20-%20trainInputMin%5B1%5D%29%5D%29%3B%0A%09%09%7D%0A%09%7D%0A%0A%09%2F%2F%20generate%20testing%20input%20tensor%20for%20visualisation%0A%09testInput%20%3D%20tf.tensor2d%28normalizedTestInputArray%2C%20%5BnormalizedTestInputArray.length%2C%202%5D%29%3B%0A%09%2F%2F%09testInput.print%28%29%3B%0A%7D%0A%0A%0A%2F%2F%0A%2F%2F%20build%20neural%20network%20model%20and%20define%20training%0A%2F%2F%0Afunction%20compileModel%28%29%20%7B%0A%09%2F%2F%20neural%20network%20structure%0A%09model%20%3D%20tf.sequential%28%7B%0A%09%09layers%3A%20%5B%0A%09%09%09tf.layers.dense%28%7B%0A%09%09%09%09name%3A%20%27HiddenLayer1%27%2C%0A%09%09%09%09inputShape%3A%20%5B2%5D%2C%0A%09%09%09%09units%3A%20ANZAHL_HIDDEN_NEURONS%2C%0A%09%09%09%09activation%3A%20%27tanh%27%0A%09%09%09%7D%29%2C%0A%09%09%09tf.layers.dense%28%7B%0A%09%09%09%09name%3A%20%27OutputLayer%27%2C%0A%09%09%09%09units%3A%201%2C%0A%09%09%09%09activation%3A%20%27sigmoid%27%0A%09%09%09%7D%29%0A%09%09%5D%0A%09%7D%29%3B%0A%0A%09%2F%2F%20neural%20network%20training%0A%09model.compile%28%7B%0A%09%09optimizer%3A%20tf.train.sgd%28LERNRATE%29%2C%0A%09%09loss%3A%20tf.losses.meanSquaredError%2C%0A%09%09metrics%3A%20%5B%27mse%27%5D%2C%0A%09%7D%29%3B%0A%7D%0A%0A%0A%2F%2F%0A%2F%2F%20train%20neural%20network%0A%2F%2F%0Aasync%20function%20trainModel%28%29%20%7B%0A%09await%20model.fit%28%0A%09%09trainInput%2C%20trainOutput%2C%20%7B%0A%09%09%09epochs%3A%20ANZAHL_EPOCHEN%2C%0A%09%09%09shuffle%3A%20true%2C%0A%09%09%09callbacks%3A%20%5B%7B%0A%09%09%09%09onEpochEnd%3A%20async%28epoch%2C%20logs%29%20%3D%3E%20%7B%0A%09%09%09%09%09%2F%2F%20remember%20epoch%20number%20if%20interrupted%0A%09%09%09%09%09actualEpoch%20%3D%20epoch%20%2B%201%3B%0A%09%09%09%09%09actualLogs%20%3D%20logs%3B%0A%09%09%09%09%09%2F%2F%20initiate%20graphic%20update%0A%09%09%09%09%09if%20%28%28%28actualEpoch%29%20%25%20EPOCHEN_FUER_GRAFIK_UPDATE%20%3D%3D%3D%200%29%20%7C%7C%20%28epoch%20%3D%3D%3D%200%29%29%20%7B%0A%09%09%09%09%09%09drawPrediction%28actualEpoch%2C%20logs.loss%29%3B%0A%09%09%09%09%09%7D%0A%09%09%09%09%7D%0A%09%09%09%7D%2C%20%5D%0A%09%09%7D%0A%09%29%3B%0A%7D%0A%0A%0A%2F%2F%0A%2F%2F%20calculate%20percentage%20of%20correct%20classifications%0A%2F%2F%0Afunction%20calculatePercentageCorrect%28predictedOutput%2C%20trueOutput%29%20%7B%0A%09let%20correct%20%3D%200%3B%0A%09let%20rejected%20%3D%200%3B%0A%09for%20%28i%20%3D%200%3B%20i%20%3C%20predictedOutput.length%3B%20i%2B%2B%29%20%7B%0A%09%09if%20%28predictedOutput%5Bi%5D%20%3C%20%281%20-%20THRESHOLD%29%20%26%26%20predictedOutput%5Bi%5D%20%3E%20THRESHOLD%29%20%7B%0A%09%09%09rejected%20%3D%20rejected%20%2B%201%3B%0A%09%09%7D%20else%20%7B%0A%09%09%09if%20%28%28trueOutput%5Bi%5D%20%3D%3D%3D%201%20%26%26%20predictedOutput%5Bi%5D%20%3E%3D%200.5%29%20%7C%7C%20%28trueOutput%5Bi%5D%20%3D%3D%3D%200%20%26%26%20predictedOutput%5Bi%5D%20%3C%200.5%29%29%20%7B%0A%09%09%09%09correct%20%3D%20correct%20%2B%201%3B%0A%09%09%09%7D%0A%09%09%7D%0A%09%7D%0A%09return%20%7B%0A%09%09correct%3A%20Math.round%28correct%20%2F%20%28predictedOutput.length%20-%20rejected%29%20%2a%20100%29%2C%0A%09%09rejected%3A%20Math.round%28rejected%20%2F%20predictedOutput.length%20%2a%20100%29%0A%09%7D%3B%0A%7D%0A%0A%0A%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%2F%2F%20FUNCTIONS%20FOR%20VISUALISATION%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%0A%0A%2F%2F%0A%2F%2F%20decision%20boundary%20and%20network%20output%0A%2F%2F%0Afunction%20drawPrediction%28epoch%2C%20mseTrain%29%20%7B%0A%09%2F%2F%20make%20predictions%20with%20neural%20network%0A%09let%20training%20%3D%20model.predict%28trainInput%29.arraySync%28%29%3B%0A%09let%20validation%20%3D%20model.predict%28validInput%29.arraySync%28%29%3B%0A%09let%20prediction%20%3D%20model.predict%28testInput%29.arraySync%28%29%3B%0A%0A%09%2F%2F%20calculate%20mse%20and%20percentages%20of%20correct%20classifications%0A%09let%20trainCorrect%20%3D%20calculatePercentageCorrect%28training%2C%20trainOutputArray%29%3B%0A%09let%20validCorrect%20%3D%20calculatePercentageCorrect%28validation%2C%20validOutputArray%29%3B%0A%0A%09%2F%2F%20decision%20boundary%20and%20input%20feature%20space%0A%09decisionBuffer.noStroke%28%29%3B%0A%09let%20element%20%3D%200%3B%0A%09for%20%28i%20%3D%200%3B%20i%20%3C%20NUM_DATA_PIXEL%20%2B%201%3B%20i%20%3D%20i%20%2B%201%29%20%7B%0A%09%09for%20%28j%20%3D%200%3B%20j%20%3C%20NUM_DATA_PIXEL%20%2B%201%3B%20j%20%3D%20j%20%2B%201%29%20%7B%0A%09%09%09%2F%2F%20transform%20neural%20network%20output%20into%20a%20color%0A%09%09%09if%20%28prediction%5Belement%5D%5B0%5D%20%3C%20%281%20-%20THRESHOLD%29%20%26%26%20prediction%5Belement%5D%5B0%5D%20%3E%20THRESHOLD%29%20%7B%0A%09%09%09%09decisionBuffer.fill%28%22white%22%29%3B%0A%09%09%09%7D%20else%20%7B%0A%09%09%09%09if%20%28prediction%5Belement%5D%5B0%5D%20%3E%200.5%29%20%7B%0A%09%09%09%09%09decisionBuffer.fill%28%22lightgreen%22%29%3B%0A%09%09%09%09%7D%20else%20%7B%0A%09%09%09%09%09decisionBuffer.fill%28%22lightblue%22%29%3B%0A%09%09%09%09%7D%0A%09%09%09%7D%0A%09%09%09%2F%2F%20check%20for%20decision%20boundary%20and%20alter%20color%0A%09%09%09if%20%28%28element%20%25%20%28NUM_DATA_PIXEL%20%2B%201%29%29%20%21%3D%3D%200%20%26%26%20%28%28prediction%5Belement%5D%5B0%5D%20%3E%200.5%20%26%26%20prediction%5Belement%20-%201%5D%5B0%5D%20%3C%3D%200.5%29%20%7C%7C%20%28prediction%5Belement%5D%5B0%5D%20%3C%3D%200.5%20%26%26%20prediction%5Belement%20-%201%5D%5B0%5D%20%3E%200.5%29%29%29%20%7B%0A%09%09%09%09decisionBuffer.fill%28%27red%27%29%3B%0A%09%09%09%7D%0A%09%09%09if%20%28element%20%3E%3D%20NUM_DATA_PIXEL%20%2B%201%20%26%26%20%28%28prediction%5Belement%5D%5B0%5D%20%3E%200.5%20%26%26%20prediction%5Belement%20-%20%28NUM_DATA_PIXEL%20%2B%201%29%5D%5B0%5D%20%3C%3D%200.5%29%20%7C%7C%20%28prediction%5Belement%5D%5B0%5D%20%3C%3D%200.5%20%26%26%20prediction%5Belement%20-%20%28NUM_DATA_PIXEL%20%2B%201%29%5D%5B0%5D%20%3E%200.5%29%29%29%20%7B%0A%09%09%09%09decisionBuffer.fill%28%27red%27%29%3B%0A%09%09%09%7D%0A%09%09%09decisionBuffer.rect%28DATA_SCALE%20%2a%20i%20%2F%20NUM_DATA_PIXEL%20%2a%20DATA_RANGE%20-%20PIXEL_SIZE%20%2F%202%2C%20DATA_SCALE%20%2a%20%2810%20-%20j%20%2F%20NUM_DATA_PIXEL%20%2a%20DATA_RANGE%29%20-%20PIXEL_SIZE%20%2F%202%2C%20PIXEL_SIZE%2C%20PIXEL_SIZE%29%3B%0A%09%09%09element%20%3D%20element%20%2B%201%3B%0A%09%09%7D%0A%09%7D%0A%09image%28decisionBuffer%2C%200%2C%200%29%3B%0A%09image%28decisionBuffer%2C%20DATA_WINDOW_SIZE%2C%200%29%3B%0A%0A%09%2F%2F%20draw%20training%20and%20validation%20samples%0A%09image%28trainBuffer%2C%200%2C%200%29%3B%0A%09image%28validBuffer%2C%20DATA_WINDOW_SIZE%2C%200%29%3B%0A%0A%09%2F%2F%20add%20lables%20to%20training%20and%20validation%20feature%20space%0A%09noStroke%28%29%3B%0A%09text%28%22Training%3A%20%22%20%2B%20trainCorrect.correct%20%2B%20%22%25%20%E2%9C%94%EF%B8%8F%EF%B8%8F%2C%20%22%20%2B%20trainCorrect.rejected%20%2B%20%22%25%20%F0%9F%97%91%22%2C%202%20%2a%20PIXEL_SIZE%2C%204%20%2a%20PIXEL_SIZE%29%3B%0A%09text%28%22Validation%3A%20%22%20%2B%20validCorrect.correct%20%2B%20%22%25%20%E2%9C%94%EF%B8%8F%2C%20%22%20%2B%20validCorrect.rejected%20%2B%20%22%25%20%F0%9F%97%91%22%2C%20DATA_WINDOW_SIZE%20%2B%202%20%2a%20PIXEL_SIZE%2C%204%20%2a%20PIXEL_SIZE%29%3B%0A%0A%09%2F%2F%20print%20training%20and%20validation%20results%20to%20console%0A%09console.log%28%22%7C%7C%20%22%20%2B%20epoch.toString%28%29.padStart%286%2C%20%22%20%22%29%20%2B%20%22%20%7C%7C%20%22%20%2B%20trainCorrect.correct.toString%28%29.padStart%286%2C%20%22%20%22%29%20%2B%20%22%25%20%7C%20%22%20%2B%20trainCorrect.rejected.toString%28%29.padStart%287%2C%20%22%20%22%29%20%2B%20%22%25%20%7C%7C%20%22%20%2B%20validCorrect.correct.toString%28%29.padStart%286%2C%20%22%20%22%29%20%2B%20%22%25%20%7C%20%22%20%2B%20validCorrect.rejected.toString%28%29.padStart%287%2C%20%22%20%22%29%20%2B%20%22%25%20%7C%7C%22%29%3B%0A%7D%0A%0A%0A%2F%2F%0A%2F%2F%20draw%20data%20in%20graphic%20buffer%0A%2F%2F%0Afunction%20drawDataInBuffer%28inputData%2C%20outputData%2C%20buffer%29%20%7B%0A%09buffer.noFill%28%29%3B%0A%09buffer.strokeWeight%28PIXEL_SIZE%20%2F%202%29%3B%0A%09buffer.rect%280%2C%200%2C%20DATA_WINDOW_SIZE%2C%20DATA_WINDOW_SIZE%29%3B%0A%09for%20%28i%20%3D%200%3B%20i%20%3C%20inputData.length%3B%20i%2B%2B%29%20%7B%0A%09%09if%20%28outputData%5Bi%5D%20%3D%3D%3D%201%29%20%7B%0A%09%09%09%2F%2F%20green%20circle%20for%20output%20lable%20%3D%3D%3D%201%0A%09%09%09buffer.stroke%28%22darkgreen%22%29%3B%0A%09%09%09buffer.circle%28DATA_SCALE%20%2a%20inputData%5Bi%5D%5B0%5D%2C%20DATA_SCALE%20%2a%20%2810%20-%20inputData%5Bi%5D%5B1%5D%29%2C%202%20%2a%20PIXEL_SIZE%29%3B%0A%09%09%7D%20else%20%7B%0A%09%09%09%2F%2F%20blue%20cross%20for%20output%20lable%20%3D%3D%3D%200%0A%09%09%09buffer.stroke%28%22blue%22%29%3B%0A%09%09%09buffer.line%28DATA_SCALE%20%2a%20inputData%5Bi%5D%5B0%5D%20%2B%20PIXEL_SIZE%2C%20DATA_SCALE%20%2a%20%2810%20-%20inputData%5Bi%5D%5B1%5D%29%20%2B%20PIXEL_SIZE%2C%20DATA_SCALE%20%2a%20inputData%5Bi%5D%5B0%5D%20-%20PIXEL_SIZE%2C%20DATA_SCALE%20%2a%20%2810%20-%20inputData%5Bi%5D%5B1%5D%29%20-%20PIXEL_SIZE%29%3B%0A%09%09%09buffer.line%28DATA_SCALE%20%2a%20inputData%5Bi%5D%5B0%5D%20%2B%20PIXEL_SIZE%2C%20DATA_SCALE%20%2a%20%2810%20-%20inputData%5Bi%5D%5B1%5D%29%20-%20PIXEL_SIZE%2C%20DATA_SCALE%20%2a%20inputData%5Bi%5D%5B0%5D%20-%20PIXEL_SIZE%2C%20DATA_SCALE%20%2a%20%2810%20-%20inputData%5Bi%5D%5B1%5D%29%20%2B%20PIXEL_SIZE%29%3B%0A%09%09%7D%0A%09%7D%0A%7D%0A%0A%0A%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%2F%2F%20MAIN%20PROGRAM%0A%2F%2F%20%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%2a%0A%0A%0A%2F%2F%0A%2F%2F%20p5.js%20setup%28%29%0A%2F%2F%0Aasync%20function%20setup%28%29%20%7B%20%2F%2Fnoprotect%20%28for%20large%20arrays%29%0A%09%2F%2F%20initiate%20console%20output%0A%09console.log%28%22%7C%7C%20%20%20%20%20%20%20%20%7C%7C%20%20%20%20%20%20Training%20%20%20%20%20%20%7C%7C%20%20%20%20%20Validation%20%20%20%20%20%7C%7C%22%29%3B%0A%09console.log%28%22%7C%7C%20Epoche%20%7C%7C%20korrekt%20%7C%20rejected%20%7C%7C%20korrekt%20%7C%20rejected%20%7C%7C%22%29%3B%0A%0A%09%2F%2F%20create%20canvas%0A%09createCanvas%282%20%2a%20DATA_WINDOW_SIZE%2C%20DATA_WINDOW_SIZE%29%3B%0A%09textSize%28PIXEL_SIZE%20%2a%203%29%3B%0A%0A%09%2F%2F%20create%20all%20grafic%20buffers%0A%09trainBuffer%20%3D%20createGraphics%28DATA_WINDOW_SIZE%2C%20DATA_WINDOW_SIZE%29%3B%0A%09validBuffer%20%3D%20createGraphics%28DATA_WINDOW_SIZE%2C%20DATA_WINDOW_SIZE%29%3B%0A%09decisionBuffer%20%3D%20createGraphics%28DATA_WINDOW_SIZE%2C%20DATA_WINDOW_SIZE%29%3B%0A%0A%09%2F%2F%20draw%20initial%20training%20and%20validation%20buffer%0A%09drawDataInBuffer%28trainInputArray%2C%20trainOutputArray%2C%20trainBuffer%29%3B%0A%09drawDataInBuffer%28validInputArray%2C%20validOutputArray%2C%20validBuffer%29%3B%0A%09image%28trainBuffer%2C%200%2C%200%29%3B%0A%09image%28validBuffer%2C%20DATA_WINDOW_SIZE%2C%200%29%3B%0A%0A%09%2F%2F%20data%20preprocessing%0A%09generateTensors%28%29%3B%0A%0A%09%2F%2F%20define%20model%20and%20training%0A%09compileModel%28%29%3B%0A%0A%09%2F%2F%20train%20and%20visualise%20neural%20network%0A%09await%20trainModel%28%29%3B%0A%0A%09%2F%2F%20end%20of%20training%0A%09console.log%28%22Das%20Training%20ist%20beendet%20%3A-%29%22%29%3B%0A%0A%7D%0A%0A%0A%2F%2F%0A%2F%2F%20p5.js%20keyPressed%28%29%20ESC%20%3D%20emergency%20stop%0A%2F%2F%0Afunction%20keyPressed%28%29%20%7B%0A%09if%20%28keyCode%20%3D%3D%3D%2027%29%20%7B%20%2F%2F%20ESC%20key%0A%09%09%2F%2F%20initiate%20stop%20of%20training%20after%20next%20epoch%0A%09%09model.stopTraining%20%3D%20true%3B%0A%09%09%2F%2F%20response%20to%20user%0A%09%09console.log%28%22Training%20wurde%20Abgebrochen%21%20Finales%20Resultat%3A%22%29%3B%0A%09%09%2F%2F%20draw%20final%20Prediction%0A%09%09drawPrediction%28actualEpoch%2C%20actualLogs.loss%29%3B%0A%09%7D%0A%7D&css=undefined&html=%3Cscript%20src%3D%22https%3A%2F%2Fapp.exorciser.ch%2Flib%2Fp5.js%22%3E%3C%2Fscript%3E%0A%3Cscript%20src%3D%22https%3A%2F%2Fcdn.jsdelivr.net%2Fnpm%2F%40tensorflow%2Ftfjs%40latest%2Fdist%2Ftf.min.js%22%3E%3C%2Fscript%3E&autorun=off&height=500px#OverlapDetection}} |
</WRAP> | </WRAP> |
| |
💡 Die Klassifikation von Fischen ist nicht nur für den Fischfang von Bedeutung. Immer mehr Regierungen fühlen sich dazu verpflichtet, ein Gleichgewicht zwischen Ökosystem und Fischfang aufrechtzuerhalten. Dazu werden auch Unterwasserroboter eingesetzt, welche Fische und Fischschwärme fotografieren, um Rückschlüsse bezüglich Fischvorkommen und insbesondere gefährdeten Fischarten ziehen zu können. Basierend auf diesen Informationen können Fangkontingente ausgesprochen werden. | 💡 Die Klassifikation von Fischen ist nicht nur für den Fischfang von Bedeutung. Immer mehr Regierungen fühlen sich dazu verpflichtet, ein Gleichgewicht zwischen Ökosystem und Fischfang aufrechtzuerhalten. Dazu werden auch Unterwasserroboter eingesetzt, welche Fische und Fischschwärme fotografieren, um Rückschlüsse bezüglich Fischvorkommen und insbesondere gefährdeten Fischarten ziehen zu können. Basierend auf diesen Informationen können Fangkontingente ausgesprochen werden. |
| |
🐟 Einen Überblick über die aktuelle Forschung zur Fischklassifizierung gibt z.B. die englischsprachige Publikation [[https://www.sciencedirect.com/science/article/pii/S1319157820304195|A survey on fish classification techniques]] von Mutasem K. Alsmadi und Ibrahim Almarashdeh((Mutasem K. Alsmadi, Ibrahim Almarashdeh, "A survey on fish classification techniques", Journal of King Saud University - Computer and Information Sciences, Volume 24, Issue 5, Pages 1625-1638, May 2022 https://doi.org/10.1016/j.jksuci.2020.07.005 [aufgerufen am 14.12.2023].)). | 🐟 Einen Überblick über die Forschung zur Fischklassifizierung gibt z.B. die englischsprachige Publikation [[https://www.sciencedirect.com/science/article/pii/S1319157820304195|A survey on fish classification techniques]] von Mutasem K. Alsmadi und Ibrahim Almarashdeh((Mutasem K. Alsmadi, Ibrahim Almarashdeh, "A survey on fish classification techniques", Journal of King Saud University - Computer and Information Sciences, Volume 24, Issue 5, Pages 1625-1638, May 2022 https://doi.org/10.1016/j.jksuci.2020.07.005 [aufgerufen am 14.12.2023].)). |
| |
| \\ |
| |
| ===== - Fortsetzung möglich... ====== |
| |
| Im [[:p:ki:fische_ki|🐟 Zusatzkapitel]] vergleichst du das neuronale Netz für die Fische mit modernen KI-Chatbots und überlegst dir, was du daraus für KI im Allgemeinen lernen kannst. |
| |
\\ | \\ |
=== Eigene Notizen === | === Eigene Notizen === |
{{gem/quill#404015cfa8640423}} | {{gem/quill#404015cfa8640423}} |