scikit-learn: Perceptron


Difficulty: 2 | Problem written by peter.washington

Educational Resource: https://towardsdatascience.com/a-beginners-guide-to-scikit-learn-14b7e51d71a4

Problem reported in interviews at


Using the sklearn library, first load in the digits dataset: https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_digits.html

Next, train a Perceptron linear model with the random state provided as input and the following stopping criteria for training:

loss > previous_loss - 0.02

Return the mean accuracy of the classifier on this training data using the score method. 

See scikit-learn's documentation for the Perceptron model: https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Perceptron.html

Observe how much the random state can affect the training results.

Note: this problem may take a few seconds to run due to training time.

Sample Input:
<class 'int'>
random_state: 1

Expected Output:
<class 'float'>

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numpy has been already imported as np (import numpy as np)