Preprocessing includes imputing missing values. Analyze Data with plotting box plot to find outliers and Correlation Matrix.
Count Accuracy with Accuracy count and K-Fold Cross Validation. Accuracy obtained is 75% and K-Fold Cross Validation mean result obtained is 83.33%
Test set is then visualized with scatter plot.
KNN is built using python programming language. KNN implementation can be found in "K-nearest-neighbout.ipynb" Dataset can be found in "dataset.csv" and data train can be found in "Data Train.csv".