To Write a program to implement k-Nearest Neighbour algorithm to classify the iris data set. Print both correct and wrong predictions. Java/Python ML library classes can be used for this problem.
Program import csv import random import math import operator def loadDataset(filename, split, trai…
Explore more »
To Apply EM algorithm to cluster a set of data stored in a .CSV file. Use the same data set for clustering using k-Means algorithm. Compare the results of these two algorithms and comment on the quality of clustering. You can add Java/Python ML library classes/API in the program.
Program import numpy as np import matplotlib.pyplot as plt from sklearn.datasets.samples_generator…
Explore more »
To Write a program to construct a Bayesian network considering medical data. Use this model to demonstrate the diagnosis of heart patients using standard Heart Disease Data Set. You can use Java/Python ML library classes/API.
Program From pomegranate import* Asia=DiscreteDistribution({ „True‟:0.5, „False‟:0.5 }) Tubercul…
Explore more »
To Assuming a set of documents that need to be classified, use the naïve Bayesian Classifier model to perform this task. Built-in Java classes/API can be used to write the program. Calculate the accuracy, precision, and recall for your data set.
Program import pandas as pd msg=pd.read_csv('naivetext1.csv',names=['message','…
Explore more »
To Write a program to implement the naïve Bayesian classifier for a sample training data set stored as a .CSV file. Compute the accuracy of the classifier, considering few test data sets.
Program import csv import random import math def loadCsv(filename): lines = csv.reader(open(filena…
Explore more »
To Build an Artificial Neural Network by implementing the Backpropagation algorithm and test the same using appropriate data sets.
Program import numpy as np X = np.array(([2, 9], [1, 5], [3, 6]), dtype=float) y = np.array(([92],…
Explore more »
write a program to demonstrate the working of the decision tree based ID3 algorithm. Use an appropriate data set for building the decision tree and apply this knowledge to classify a new sample.
Program import numpy as np import math from data_loader import read_data class Node: def init (sel…
Explore more »
Write a program for a given set of training data examples stored in a .CSV file, implement and demonstrate the Candidate-Elimination algorithm to output a description of the set of all hypotheses consistent with the training examples.
Program class Holder: factors={} #Initialize an empty dictionary attributes = () #declaration of d…
Explore more »
Write a program for Implement and demonstrate the FIND-S algorithm for finding the most specific hypothesis based on a given set of training data samples. Read the training data from a .CSV file.
Program import csv with open('tennis.csv', 'r') as f: reader = csv.reader(f) your_…
Explore more »