코드 변경 내용을 요약한 커밋 메시지입니다.

test/bean.py

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+import os
+
+from keras.layers import Dense
+from keras.models import Sequential
+from keras.utils import to_categorical
+from sklearn.model_selection import train_test_split
+from tensorflow import keras
+from ucimlrepo import fetch_ucirepo
+
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
+os.environ["TF_FORCE_GPU_ALLOW_GROWTH"] = "true"
+
+
+def make_model():
+    model = Sequential()
+    model.add(Dense(12, input_dim=16, activation="relu"))
+    model.add(Dense(8, activation="relu"))
+    model.add(Dense(7, activation="softmax"))
+
+    return model
+
+
+def get_data():
+    # fetch dataset
+    dry_bean_dataset = fetch_ucirepo(id=602)
+
+    # data (as pandas dataframes)
+    X = dry_bean_dataset.data.features
+    y = dry_bean_dataset.data.targets
+
+    x = X.to_numpy()
+    # object to categorical
+
+    x = x.astype("float32")
+
+    y_class = to_categorical(y)
+
+    # metadata
+    # print(dry_bean_dataset.metadata)
+
+    # variable information
+    # print(dry_bean_dataset.variables)
+
+    # print(X.head())
+    # print(y.head())
+    # y_class = to_categorical(y)
+
+    x_train, x_test, y_train, y_test = train_test_split(
+        x, y_class, test_size=0.2, random_state=42, shuffle=True
+    )
+    return x_train, x_test, y_train, y_test
+
+
+x_train, x_test, y_train, y_test = get_data()
+model = make_model()
+early_stopping = keras.callbacks.EarlyStopping(
+    patience=10, min_delta=0.001, restore_best_weights=True
+)
+
+
+model.compile(
+    loss="sparse_categorical_crossentropy",
+    optimizer="adam",
+    metrics=["accuracy", "mse"],
+)
+
+model.summary()
+
+history = model.fit(
+    x_train, y_train, epochs=150, batch_size=10, callbacks=[early_stopping]
+)
+score = model.evaluate(x_test, y_test, verbose=2)