shreyashsomvanshi / machine-hack-practice-problems

Machine Hack Problems

Machine-Hack-Problems

Machine Hack Problems

My Machine Hack Profile: https://machinehack.com/user/63e66c416018ef32de78c4d0

machine-hack-practice-problems's Issues

Incorrect merge in List section #30

_30. Rounding of float elements in a list.py

invalid results on MH

Wrong output!

Arrays/#82. Difference between the mean and median of two sorted arrays
incorrect output .

119. Update a set.py Incorrect output for 1st test case

119. Update a set.py Incorrect output for 1st test case

91. Add matrices.py correct output for test cases but not getting accepted!

Matrix/ 91. Add matrices.py is giving correct output for test cases but not getting accepted!

Add other simplest and relevant answer to strings space counts

61 strings space counts

Try inbuilt method for median in statistics 160th

Try inbuilt method for median in statistics 160th @ShreyashSomvanshi

Answer didnt get accepted

ML/462. Coefficients of the Logistic Regression model.py

Next easy problem - 907. Evaluate classification model performance.py

'''
You are given a list of ground truth labels y_true_list and a list of predicted labels y_pred_list for multiple classes.
Write a function that takes these two lists as input and returns a pandas DataFrame containing evaluation metrics for each class.
The function should calculate the ROC AUC score, precision, and recall for each class. The input lists may contain multiple elements,
each corresponding to a different class. The function should return a DataFrame with one row per class and three columns containing the
evaluation metrics.

Example 1:

Input:
y_true_list = [[0, 1, 1, 0, 1],
[1, 1, 0, 0],
[0, 0, 1, 1, 0, 1]]
y_pred_list = [[0, 1, 0, 0, 1],
[1, 1, 1, 0],
[0, 0, 1, 0, 1, 1]]

Output:

ROC AUC Score Precision Recall
0 0.833333 0.866667 0.800000
1 0.750000 0.833333 0.750000
2 0.666667 0.666667 0.666667

Example 2:

Input:

y_true_list = [[1, 0, 0, 1, 1],
[0, 1, 0, 1],
[1, 1, 0, 0, 1, 0]]
y_pred_list = [[1, 0, 1, 1, 1],
[0, 1, 0, 0],
[1, 0, 0, 1, 1, 1]]
Output:

ROC AUC Score Precision Recall
0 0.75 0.850000 0.80
1 0.75 0.833333 0.75
2 0.50 0.500000 0.50

Constraints: The output should be in the pandas DataFrame.

'''

Solution: