arshren

#Import required libraries
import tensorflow as tf
from keras.datasets import mnist

#Creating the MNIST Dataset
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train, x_test= x_train/255.0, x_test/255.0
x_train=x_train[...,tf.newaxis].astype('float32')
x_test=x_test[...,tf.newaxis].astype('float32')

arshren

from sklearn import datasets
from sklearn.semi_supervised import LabelPropagation
from sklearn.metrics import confusion_matrix, classification_report
import numpy as np

rnd = np.random.RandomState(42)
# load the cancer dataset
cancer = datasets.load_breast_cancer()

# Randomly unlabel some records in the dataset