The lab4-ml from utki96

lab4-ml's Introduction

System requirements to build and run the project:

Change the working directory to the root folder of this project.
Execute command: mvn clean
Execute command: mvn package
Now you have an executable jar in "./target/learn-1.jar"
Run this jar file by this command:
java -jar target/learn-1.jar [k=%d] [c=%d] [d=%s] [test=%s] [train=%s] [v] [centroid_values]

k : Indicates the number of points to use for knn.
Eg: k=3. Make sure not to add spaces in between
c : Indicates the Laplacian correction for Naive-Bayes.
Eg: c=1. Make sure not to add spaces in between
train : pass the training data file as this parameter.
Eg: train=/home/utkarshtyg/Documents/knn/knn1.train.txt. Make sure not to add spaces in between
test : pass the testing data file as this parameter.
Eg: test=/home/utkarshtyg/Documents/knn/knn1.test.txt. Make sure not to add spaces in between
d : Indicates the distance function only for KMeans: manh(Manhattan Distance)/e2(Euc squared).
Eg: d=manh. Make sure not to add spaces in between
centroid_value: pass the centroid values only for KMeans.
Eg: 200,200,200. Make sure not to add spaces in between and to separate the dimensions with a ','.

KNN learner:
Eg: java -jar target/learn-1.jar train=/home/utkarshtyg/Documents/knn/knn1.train.txt test=/home/utkarshtyg/Documents/knn/knn1.test.txt k=3
Bayes learner:
Eg: java -jar target/learn-1.jar train=/home/utkarshtyg/Documents/bayes/ex1_train.csv test=/home/utkarshtyg/Documents/bayes/ex1_test.csv c=1 v
KMeans learner:
Eg: java -jar target/learn-1.jar train=/home/utkarshtyg/Documents/kmeans/km1.txt 0,0 200,200 500,500

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