Построить нейронную сеть из csv [закрыто] ⇐ Python

[Anonymous]

Код: Выделить всё

# Assuming you want to predict the 'SalePrice' target variable based on other features

# Extract features (X) and target variable (y)
`X = data.drop(columns=['SalePrice'])  # Assuming 'SalePrice' is
the target variable
y = data['SalePrice']`

# Perform train-test split
`X_train, X_test, y_train, y_test = train_test_split(X, y,
test_size=0.2, random_state=42)`

# Standardize features
`scaler = StandardScaler()
X_train_scaled = scaler.fit_transform(X_train)
X_test_scaled = scaler.transform(X_test)`

# Define the neural network architecture
`model = tf.keras.models.Sequential([
tf.keras.layers.Dense(128, activation='relu', input_shape=(X_train_scaled.shape[1],)),
tf.keras.layers.Dense(64, activation='relu'),
tf.keras.layers.Dense(1)  # Output layer with single neuron (for regression)
])`

# Compile the model
`model.compile(optimizer='adam', loss='mean_squared_error')`

# Train the model
`history = model.fit(X_train_scaled, y_train, epochs=50, batch_size=32, validation_split=0.2)`

# Evaluate the model on test data
`loss = model.evaluate(X_test_scaled, y_test)
print("Test Loss:", loss)`

Я получаю сообщение об ошибке KeyError: «['SalePrice'] не найдено на оси», хотя я вижу SalePrice в CSV-файле. Я пытаюсь построить нейронную сеть на основе существующих данных.

Подробнее здесь: https://stackoverflow.com/questions/783 ... k-from-csv