IMPLEMENT AND DEMONSTRATETHE 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.

FOR A GIVEN SET OF TRAINING DATA EXAMPLES STORED IN A .CSV FILE, IMPLEMENT AND DEMONSTRATE THE CANDIDATE-ELIMINATION ALGORITHMTO OUTPUT A DESCRIPTION OF THE SET OF ALL HYPOTHESES CONSISTENT WITH THE TRAINING EXAMPLES.

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 TOCLASSIFY A NEW SAMPLE.

BUILD AN ARTIFICIAL NEURAL NETWORK BY IMPLEMENTING THE BACKPROPAGATION ALGORITHM AND TEST THE SAME USING APPROPRIATE DATA SETS.

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.

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.

WRITE A PROGRAM TO CONSTRUCT ABAYESIAN 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.

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.

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.

IMPLEMENT THE NON-PARAMETRIC LOCALLY WEIGHTED REGRESSIONALGORITHM IN ORDER TO FIT DATA POINTS. SELECT APPROPRIATE DATA SET FOR YOUR EXPERIMENT AND DRAW GRAPHS.