Train Test split program

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Summary

The provided code is a train test split function, which is a crucial step in machine learning pipelines. It takes in a dataset and a test ratio, then splits the data into training and testing sets. However, there seems to be an issue with the implementation, as the function is not correctly returning the test set.

Root Cause

The root cause of the issue lies in the fact that the function is returning data.iloc[test_indices], but test_indices is not defined anywhere in the function. Instead, the function defines test_indeces, which is not used. This is likely a typo.

Why This Happens in Real Systems

This type of issue can happen in real systems due to:

  • Human error: Typos and mistakes can occur when writing code.
  • Lack of testing: If the function is not thoroughly tested, issues like this can go unnoticed.
  • Code complexity: As codebases grow, it can become harder to keep track of variable names and function calls.

Real-World Impact

The impact of this issue can be significant, as it can lead to:

  • Incorrect model evaluation: If the test set is not correctly split, the model’s performance may be overestimated or underestimated.
  • Poor model generalization: If the training set is not representative of the data, the model may not generalize well to new, unseen data.
  • Wasted resources: If the issue is not caught, it can lead to wasted resources, such as computational power and time.

Example or Code

import numpy as np
import pandas as pd

def shuffle_and_split(data, test_ratio):
    shuffled_indices = np.random.permutation(len(data))
    test_set_size = int(len(data) * test_ratio)
    test_indices = shuffled_indices[:test_set_size]
    train_indices = shuffled_indices[test_set_size:]
    return data.iloc[train_indices], data.iloc[test_indices]

How Senior Engineers Fix It

Senior engineers would fix this issue by:

  • Carefully reviewing the code: They would thoroughly review the code to catch any typos or mistakes.
  • Writing unit tests: They would write unit tests to ensure the function is working correctly.
  • Using code review tools: They would use code review tools to catch any issues before the code is merged into the main branch.

Why Juniors Miss It

Juniors may miss this issue due to:

  • Lack of experience: They may not have the experience to catch typos or mistakes.
  • Insufficient testing: They may not thoroughly test the function, which can lead to issues going unnoticed.
  • Limited knowledge: They may not have the knowledge to use code review tools or write unit tests.

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