forked from s444420/AL-2020
train.py
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from sklearn.feature_extraction import FeatureHasher
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from data import create_data_dict
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data = create_data_dict()
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print(data)
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BIN
coder/test.jpg
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BIN
coder/test.jpg
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After Width: | Height: | Size: 44 KiB |
27
coder/train.py
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27
coder/train.py
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import matplotlib.pyplot as plt
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import numpy as np
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from numpy import asarray
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from sklearn import datasets
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from sklearn.neural_network import MLPClassifier
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from sklearn.metrics import accuracy_score
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from PIL import Image
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#recznie napisane cyfry
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digits = datasets.load_digits()
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y = digits.target
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x = digits.images.reshape((len(digits.images), -1))
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x_train = x[:1000000]
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y_train = y[:1000000]
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x_test = x[1000:]
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y_test = y[1000:]
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mlp = MLPClassifier(hidden_layer_sizes=(15,), activation='logistic', alpha=1e-4,
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solver='sgd', tol=1e-4, random_state=1,
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learning_rate_init=.1, verbose=True)
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mlp.fit(x_train, y_train)
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predictions = mlp.predict(x_test)
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print(accuracy_score(y_test, predictions))
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