Sci-kit learn how to print labels for confusion matrix?

Question

So I\'m using sci-kit learn to classify some data. I have 13 different class values/categorizes to classify the data to. Now I have been able to use cross validation and print t

Answer 1

Since confusion matrix is just a numpy matrix, it does not contain any column information. What you can do is convert your matrix into a dataframe and then print this dataframe.

import pandas as pd
import numpy as np

def cm2df(cm, labels):
    df = pd.DataFrame()
    # rows
    for i, row_label in enumerate(labels):
        rowdata={}
        # columns
        for j, col_label in enumerate(labels): 
            rowdata[col_label]=cm[i,j]
        df = df.append(pd.DataFrame.from_dict({row_label:rowdata}, orient='index'))
    return df[labels]

cm = np.arange(9).reshape((3, 3))
df = cm2df(cm, ["a", "b", "c"])
print(df)

Code snippet is from https://gist.github.com/nickynicolson/202fe765c99af49acb20ea9f77b6255e

Output:

   a  b  c
a  0  1  2
b  3  4  5
c  6  7  8