idz_Ershov_Gordiyenko

8382/Gordiyenko/idz/main.py

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+"""
+    Individual project ZOO
+    Animals classification by attributes using ANN
+    Authors:
+        @Mikhail Ershov
+        @Gordiyenko Alexandr
+"""
+import matplotlib.pyplot as plt
+import pandas
+from tensorflow.keras.layers import Dense
+from tensorflow.keras.models import Sequential
+from tensorflow.keras.utils import to_categorical
+from sklearn.preprocessing import LabelEncoder
+
+# reading data
+csv_file = pandas.read_csv('zoo.csv', header=None)
+dataset = csv_file.values
+X = dataset[:, 1:17].astype(bool)
+Y = dataset[:, 17]
+
+# setting categories
+# categories = {
+#     0: ['aardvark', 'antelope', 'bear', 'boar', 'buffalo', 'calf', 'cavy', 'cheetah', 'deer', 'dolphin',
+#         'elephant', 'fruitbat', 'giraffe', 'girl', 'goat', 'gorilla', 'hamster', 'hare', 'leopard', 'lion',
+#         'lynx', 'mink', 'mole', 'mongoose', 'opossum', 'oryx', 'platypus', 'polecat', 'pony', 'porpoise',
+#         'puma', 'pussycat', 'raccoon', 'reindeer', 'seal', 'sealion', 'squirrel', 'vampire', 'vole',
+#         'wallaby', 'wolf'],
+#     1: ['chicken', 'crow', 'dove', 'duck', 'flamingo', 'gull', 'hawk', 'kiwi', 'lark', 'ostrich', 'parakeet',
+#         'penguin', 'pheasant', 'rhea', 'skimmer', 'skua', 'sparrow', 'swan', 'vulture', 'wren'],
+#     2: ['pitviper', 'seasnake', 'slowworm', 'tortoise', 'tuatara'],
+#     3: ['bass', 'carp', 'catfish', 'chub', 'dogfish', 'haddock', 'herring', 'pike', 'piranha', 'seahorse',
+#         'sole', 'stingray', 'tuna'],
+#     4: ['frog', 'frog', 'newt', 'toad'],
+#     5: ['flea', 'gnat', 'honeybee', 'housefly', 'ladybird', 'moth', 'termite', 'wasp'],
+#     6: ['clam', 'crab', 'crayfish', 'lobster', 'octopus', 'scorpion', 'seawasp', 'slug', 'starfish', 'worm']
+# }
+
+# setting Y dimension to be equal to X dimension
+# Y = [i for category in Y for i in range(len(categories)) if category in categories[i]]
+
+# setting categories
+encoder = LabelEncoder()
+encoder.fit(Y)
+encoded_Y = encoder.transform(Y)
+dummy_y = to_categorical(encoded_Y)
+
+# building model
+model = Sequential()
+model.add(Dense(16, input_dim=16, activation='relu'))
+model.add(Dense(48, activation='relu'))
+model.add(Dense(7, activation='softmax'))
+
+# setting training parameters
+model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
+
+# training model
+h = model.fit(X, dummy_y, epochs=25, batch_size=5, validation_split=0.1)
+
+# plotting training and validation accuracies and losses
+h_dict = h.history
+
+loss = h_dict['loss']
+accuracy = h_dict['accuracy']
+val_loss = h_dict['val_loss']
+val_accuracy = h_dict['val_accuracy']
+
+epochs = range(1, len(loss)+1)
+
+plt.plot(epochs, accuracy, 'bo', label='Training accuracy')
+plt.plot(epochs, val_accuracy, 'b-', label='Validation accuracy')
+plt.title('Training and validation accuracy')
+plt.xlabel('Epochs')
+plt.ylabel('Accuracy')
+plt.legend()
+plt.show()
+
+plt.plot(epochs, loss, 'bo', label='Training loss')
+plt.plot(epochs, val_loss, 'b-', label='Validation loss')
+plt.title('Training and validation loss')
+plt.xlabel('Epochs')
+plt.legend()
+plt.show()

8382/Gordiyenko/idz/zoo.csv

@@ -0,0 +1,101 @@
+aardvark,1,0,0,1,0,0,1,1,1,1,0,0,4,0,0,1,1
+antelope,1,0,0,1,0,0,0,1,1,1,0,0,4,1,0,1,1
+bass,0,0,1,0,0,1,1,1,1,0,0,1,0,1,0,0,4
+bear,1,0,0,1,0,0,1,1,1,1,0,0,4,0,0,1,1
+boar,1,0,0,1,0,0,1,1,1,1,0,0,4,1,0,1,1
+buffalo,1,0,0,1,0,0,0,1,1,1,0,0,4,1,0,1,1
+calf,1,0,0,1,0,0,0,1,1,1,0,0,4,1,1,1,1
+carp,0,0,1,0,0,1,0,1,1,0,0,1,0,1,1,0,4
+catfish,0,0,1,0,0,1,1,1,1,0,0,1,0,1,0,0,4
+cavy,1,0,0,1,0,0,0,1,1,1,0,0,4,0,1,0,1
+cheetah,1,0,0,1,0,0,1,1,1,1,0,0,4,1,0,1,1
+chicken,0,1,1,0,1,0,0,0,1,1,0,0,2,1,1,0,2
+chub,0,0,1,0,0,1,1,1,1,0,0,1,0,1,0,0,4
+clam,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,7
+crab,0,0,1,0,0,1,1,0,0,0,0,0,4,0,0,0,7
+crayfish,0,0,1,0,0,1,1,0,0,0,0,0,6,0,0,0,7
+crow,0,1,1,0,1,0,1,0,1,1,0,0,2,1,0,0,2
+deer,1,0,0,1,0,0,0,1,1,1,0,0,4,1,0,1,1
+dogfish,0,0,1,0,0,1,1,1,1,0,0,1,0,1,0,1,4
+dolphin,0,0,0,1,0,1,1,1,1,1,0,1,0,1,0,1,1
+dove,0,1,1,0,1,0,0,0,1,1,0,0,2,1,1,0,2
+duck,0,1,1,0,1,1,0,0,1,1,0,0,2,1,0,0,2
+elephant,1,0,0,1,0,0,0,1,1,1,0,0,4,1,0,1,1
+flamingo,0,1,1,0,1,0,0,0,1,1,0,0,2,1,0,1,2
+flea,0,0,1,0,0,0,0,0,0,1,0,0,6,0,0,0,6
+frog,0,0,1,0,0,1,1,1,1,1,0,0,4,0,0,0,5
+frog,0,0,1,0,0,1,1,1,1,1,1,0,4,0,0,0,5
+fruitbat,1,0,0,1,1,0,0,1,1,1,0,0,2,1,0,0,1
+giraffe,1,0,0,1,0,0,0,1,1,1,0,0,4,1,0,1,1
+girl,1,0,0,1,0,0,1,1,1,1,0,0,2,0,1,1,1
+gnat,0,0,1,0,1,0,0,0,0,1,0,0,6,0,0,0,6
+goat,1,0,0,1,0,0,0,1,1,1,0,0,4,1,1,1,1
+gorilla,1,0,0,1,0,0,0,1,1,1,0,0,2,0,0,1,1
+gull,0,1,1,0,1,1,1,0,1,1,0,0,2,1,0,0,2
+haddock,0,0,1,0,0,1,0,1,1,0,0,1,0,1,0,0,4
+hamster,1,0,0,1,0,0,0,1,1,1,0,0,4,1,1,0,1
+hare,1,0,0,1,0,0,0,1,1,1,0,0,4,1,0,0,1
+hawk,0,1,1,0,1,0,1,0,1,1,0,0,2,1,0,0,2
+herring,0,0,1,0,0,1,1,1,1,0,0,1,0,1,0,0,4
+honeybee,1,0,1,0,1,0,0,0,0,1,1,0,6,0,1,0,6
+housefly,1,0,1,0,1,0,0,0,0,1,0,0,6,0,0,0,6
+kiwi,0,1,1,0,0,0,1,0,1,1,0,0,2,1,0,0,2
+ladybird,0,0,1,0,1,0,1,0,0,1,0,0,6,0,0,0,6
+lark,0,1,1,0,1,0,0,0,1,1,0,0,2,1,0,0,2
+leopard,1,0,0,1,0,0,1,1,1,1,0,0,4,1,0,1,1
+lion,1,0,0,1,0,0,1,1,1,1,0,0,4,1,0,1,1
+lobster,0,0,1,0,0,1,1,0,0,0,0,0,6,0,0,0,7
+lynx,1,0,0,1,0,0,1,1,1,1,0,0,4,1,0,1,1
+mink,1,0,0,1,0,1,1,1,1,1,0,0,4,1,0,1,1
+mole,1,0,0,1,0,0,1,1,1,1,0,0,4,1,0,0,1
+mongoose,1,0,0,1,0,0,1,1,1,1,0,0,4,1,0,1,1
+moth,1,0,1,0,1,0,0,0,0,1,0,0,6,0,0,0,6
+newt,0,0,1,0,0,1,1,1,1,1,0,0,4,1,0,0,5
+octopus,0,0,1,0,0,1,1,0,0,0,0,0,8,0,0,1,7
+opossum,1,0,0,1,0,0,1,1,1,1,0,0,4,1,0,0,1
+oryx,1,0,0,1,0,0,0,1,1,1,0,0,4,1,0,1,1
+ostrich,0,1,1,0,0,0,0,0,1,1,0,0,2,1,0,1,2
+parakeet,0,1,1,0,1,0,0,0,1,1,0,0,2,1,1,0,2
+penguin,0,1,1,0,0,1,1,0,1,1,0,0,2,1,0,1,2
+pheasant,0,1,1,0,1,0,0,0,1,1,0,0,2,1,0,0,2
+pike,0,0,1,0,0,1,1,1,1,0,0,1,0,1,0,1,4
+piranha,0,0,1,0,0,1,1,1,1,0,0,1,0,1,0,0,4
+pitviper,0,0,1,0,0,0,1,1,1,1,1,0,0,1,0,0,3
+platypus,1,0,1,1,0,1,1,0,1,1,0,0,4,1,0,1,1
+polecat,1,0,0,1,0,0,1,1,1,1,0,0,4,1,0,1,1
+pony,1,0,0,1,0,0,0,1,1,1,0,0,4,1,1,1,1
+porpoise,0,0,0,1,0,1,1,1,1,1,0,1,0,1,0,1,1
+puma,1,0,0,1,0,0,1,1,1,1,0,0,4,1,0,1,1
+pussycat,1,0,0,1,0,0,1,1,1,1,0,0,4,1,1,1,1
+raccoon,1,0,0,1,0,0,1,1,1,1,0,0,4,1,0,1,1
+reindeer,1,0,0,1,0,0,0,1,1,1,0,0,4,1,1,1,1
+rhea,0,1,1,0,0,0,1,0,1,1,0,0,2,1,0,1,2
+scorpion,0,0,0,0,0,0,1,0,0,1,1,0,8,1,0,0,7
+seahorse,0,0,1,0,0,1,0,1,1,0,0,1,0,1,0,0,4
+seal,1,0,0,1,0,1,1,1,1,1,0,1,0,0,0,1,1
+sealion,1,0,0,1,0,1,1,1,1,1,0,1,2,1,0,1,1
+seasnake,0,0,0,0,0,1,1,1,1,0,1,0,0,1,0,0,3
+seawasp,0,0,1,0,0,1,1,0,0,0,1,0,0,0,0,0,7
+skimmer,0,1,1,0,1,1,1,0,1,1,0,0,2,1,0,0,2
+skua,0,1,1,0,1,1,1,0,1,1,0,0,2,1,0,0,2
+slowworm,0,0,1,0,0,0,1,1,1,1,0,0,0,1,0,0,3
+slug,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,7
+sole,0,0,1,0,0,1,0,1,1,0,0,1,0,1,0,0,4
+sparrow,0,1,1,0,1,0,0,0,1,1,0,0,2,1,0,0,2
+squirrel,1,0,0,1,0,0,0,1,1,1,0,0,2,1,0,0,1
+starfish,0,0,1,0,0,1,1,0,0,0,0,0,5,0,0,0,7
+stingray,0,0,1,0,0,1,1,1,1,0,1,1,0,1,0,1,4
+swan,0,1,1,0,1,1,0,0,1,1,0,0,2,1,0,1,2
+termite,0,0,1,0,0,0,0,0,0,1,0,0,6,0,0,0,6
+toad,0,0,1,0,0,1,0,1,1,1,0,0,4,0,0,0,5
+tortoise,0,0,1,0,0,0,0,0,1,1,0,0,4,1,0,1,3
+tuatara,0,0,1,0,0,0,1,1,1,1,0,0,4,1,0,0,3
+tuna,0,0,1,0,0,1,1,1,1,0,0,1,0,1,0,1,4
+vampire,1,0,0,1,1,0,0,1,1,1,0,0,2,1,0,0,1
+vole,1,0,0,1,0,0,0,1,1,1,0,0,4,1,0,0,1
+vulture,0,1,1,0,1,0,1,0,1,1,0,0,2,1,0,1,2
+wallaby,1,0,0,1,0,0,0,1,1,1,0,0,2,1,0,1,1
+wasp,1,0,1,0,1,0,0,0,0,1,1,0,6,0,0,0,6
+wolf,1,0,0,1,0,0,1,1,1,1,0,0,4,1,0,1,1
+worm,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,7
+wren,0,1,1,0,1,0,0,0,1,1,0,0,2,1,0,0,2