Here you can get 7TH SEM CSE ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING LAB PROGRAMS code | VTU 7TH SEM | VTU CSE LABORATORY.
Implementation of A* Algorithm
Implementation of AO* Algorithm
1. 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 2. 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 -3] 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 4] BUILD AN ARTIFICIAL NEURAL NETWORK BY IMPLEMENTING THE BACKPROPAGATION ALGORITHM AND TEST THE SAME USING APPROPRIATE DATASETS.
Program 5. 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 6. 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 7. WRITE A PROGRAM TO CONSTRUCT AN 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.
Program 8. 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 9. 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 10. IMPLEMENT THE NON-PARAMETRIC LOCALLY WEIGHTED REGRESSION ALGORITHM IN ORDER TO FIT DATA POINTS. SELECT THE APPROPRIATE DATA SET FOR YOUR EXPERIMENT AND DRAW GRAPHS.
