I have applied supervised learning algorithms such as regression, decision trees, KNN, Bernoulli BayesNB, naive Bayes, XGBoost to solving business problem.
Randomly partition each dataset into two parts i.e 80 - 20 sets.
For dataset 1, because we don't have the label for the test set, we will use the train set to create train and test data(i.e splitting further), then performing thr K-nearet neighbour classification.
Loading the Dataset
Exploratory Data Analysis
Visualization
Data CLeaning
Modelling: K-Nearest Neighbours CLassifier(KNN)
Optimization Techniques for KNN
Challenging the Model: Using XGBOOST
Conclusion
Loading the Dataset
Exploratory Data Analysis
Visualization
Modelling: Naive Bayes Classifier; GaussianNB
Optimizing techniques for Gaussian Naive Bayes Classifier
Modelling: Naive Bayes Classifier; Bernoulli BayesNB
Reccomendations
Challenging the Solution: XGBOOST
Conclusion