Visualize module not getting imported

A18ML0031 · September 7, 2020, 4:20pm

Hi,

I am not able import the visualize module in my notebook. I have run it from pycharm also. Still, it says that there is no module by the name of ‘visualize’

Aayushkh_333 · September 7, 2020, 7:38pm

Hey @A18ML0031, can you please share your code by uploading it on google drive and sharing the link over here ? I’ll have to look at it once.

Thanks !

A18ML0031 · September 8, 2020, 8:15am

It says that i ‘can’t post a link to that host’ . I have reported the same issue of being unable to post the drive links on another doubt as well.

A18ML0031 · September 30, 2020, 11:17am

Here is the code: https://ide.codingblocks.com/s/331012

Aayushkh_333 · September 8, 2020, 10:38am

Hey @A18ML0031, please use this import statement in your code and see if it works :

from sklearn.metrics import plot_confusion_matrix

I hope this helps !
Happy Learning !

A18ML0031 · September 8, 2020, 10:54am

I am not able to plot the confusion matrix. I have extracted the matrix in my code. How do i plot it if i am not able to import the visualze.py file in my notebook?

Aayushkh_333 · September 8, 2020, 2:59pm

What is there in your visualize.py file ? I don’t think we need a separate python module of file for printing the confusion matrix. Please refer this link to see how you can plot a confusion matrix.

I hope this clears your doubt !
Happy coding !

A18ML0031 · September 10, 2020, 11:34am

Visualize.py module is being used by Prateek Bhaiya in the video. That is what i am asking about.

A18ML0031 · September 10, 2020, 11:42am

It helps me plot the decision boundary of the same

Aayushkh_333 · September 10, 2020, 4:13pm

Hey @A18ML0031, make sure you have created the visualize.py file. Please find the file at the below link. Also make sure to keep both the python codes in the same directory to be able to import it directly.

github.com

prateek27/deep-neural-network/blob/master/visualize.py

import matplotlib.pyplot as plt
import numpy as np

def plot_decision_boundary(model, X, y,cmap=plt.cm.jet):
    """
    Given a model(a function) and a set of points(X), corresponding labels(y), scatter the points in X with color coding
    according to y. Also use the model to predict the label at grid points to get the region for each label, and thus the 
    descion boundary.
    Example usage:
    say we have a function predict(x,other params) which makes 0/1 prediction for point x and we want to plot
    train set then call as:
    plot_decision_boundary(lambda x:predict(x,other params),X_train,Y_train)
    params(3): 
        model : a function which expectes the point to make 0/1 label prediction
        X : a (mx2) numpy array with the points
        y : a (mx1) numpy array with labels
    outputs(None)
    """
    # Set min and max values and give it some padding
    x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1

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I hope this helps !
Happy Learning !

Aayushkh_333 · September 20, 2020, 7:39am

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