Scikit-learn: How to obtain True Positive, True Negative, False Positive and False Negative

Question

My problem:

I have a dataset which is a large JSON file. I read it and store it in the trainList variable.

Next, I pre-process

Answer 1

I wrote a version that works using only numpy. I hope it helps you.

import numpy as np

def perf_metrics_2X2(yobs, yhat):
    """
    Returns the specificity, sensitivity, positive predictive value, and 
    negative predictive value 
    of a 2X2 table.

    where:
    0 = negative case
    1 = positive case

    Parameters
    ----------
    yobs :  array of positive and negative ``observed`` cases
    yhat : array of positive and negative ``predicted`` cases

    Returns
    -------
    sensitivity  = TP / (TP+FN)
    specificity  = TN / (TN+FP)
    pos_pred_val = TP/ (TP+FP)
    neg_pred_val = TN/ (TN+FN)

    Author: Julio Cardenas-Rodriguez
    """
    TP = np.sum(  yobs[yobs==1] == yhat[yobs==1] )
    TN = np.sum(  yobs[yobs==0] == yhat[yobs==0] )
    FP = np.sum(  yobs[yobs==1] == yhat[yobs==0] )
    FN = np.sum(  yobs[yobs==0] == yhat[yobs==1] )

    sensitivity  = TP / (TP+FN)
    specificity  = TN / (TN+FP)
    pos_pred_val = TP/ (TP+FP)
    neg_pred_val = TN/ (TN+FN)

    return sensitivity, specificity, pos_pred_val, neg_pred_val