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BigCodeBench / BigCodeBench v0.1.0_hf 470c3d6b-ac38-5ed7-954f-b75c86e9e1e3

Problem

Answer published by the source. Consult the official source to check your work against its answer.

complete prompt

import tensorflow as tf
from sklearn.model_selection import KFold
from sklearn.preprocessing import MinMaxScaler

def task_func(X, y, n_splits, batch_size, epochs):
    """
    Trains a simple neural network on provided data using k-fold cross-validation.
    The network has one hidden layer with 20 neurons and ReLU activation, and
    an output layer with sigmoid activation for binary classification.

    Parameters:
        X (numpy.array): The input data.
        y (numpy.array): The target data.
        n_splits (int): The number of splits for k-fold cross-validation. Default is 5.
        batch_size (int): The size of the batch used during training. Default is 32.
        epochs (int): The number of epochs for training the model. Default is 1.

    Returns:
        list: A list containing the training history of the model for each fold. Each history
              object includes training loss and accuracy.

    Requirements:
    - tensorflow
    - sklearn.model_selection.KFold
    - sklearn.preprocessing.MinMaxScaler

    Examples:
    >>> import numpy as np
    >>> X = np.random.rand(100, 10)
    >>> y = np.random.randint(0, 2, 100)
    >>> history = task_func(X, y, 5, 32, 1)
    >>> isinstance(history, list)
    True
    >>> len(history)
    5
    >>> all('loss' in hist.history.keys() for hist in history)
    True
    """

instruct prompt

Trains a simple neural network on provided data using k-fold cross-validation. The network has one hidden layer with 20 neurons and ReLU activation, and an output layer with sigmoid activation for binary classification.
The function should output with:
    list: A list containing the training history of the model for each fold. Each history
    object includes training loss and accuracy.
You should write self-contained code starting with:

Code

import tensorflow as tf
from sklearn.model_selection import KFold
from sklearn.preprocessing import MinMaxScaler
def task_func(X, y, n_splits, batch_size, epochs):

code prompt

Code

import tensorflow as tf
from sklearn.model_selection import KFold
from sklearn.preprocessing import MinMaxScaler
def task_func(X, y, n_splits, batch_size, epochs):

entry point

task_func

libs

  • tensorflow
  • sklearn

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Source and history

task_id
470c3d6b-ac38-5ed7-954f-b75c86e9e1e3
task_key
default--v0~2e1~2e0~5fhf--470c3d6b-ac38-5ed7-954f-b75c86e9e1e3
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import