Machine Learning Project

ICS 574: Project Due: Saturday Week 14 Use Spark Machine Learning library to complete all the three parts of this project. Part A: Clustering – 7% 1. [2 pts] Find a dataset in kaggle or any other source. Make sure that each dataset is at least 500 MB. 2. [2 pt] Write a detailed description of the dataset. 3. [6 pt] Preprocess the dataset. 4. [8 pts] Using K-means algorithm to cluster the dataset. 5. [4 pts] Use the Elbow method and the Silhouette method to find the optimal K. Part B: Regression – 7% 1. [2 pts] Find one or two datasets in kaggle or any other source. Make sure that each dataset is at least 500 MB. 2. [2 pts] Write a detailed description of each dataset. 3. [6 pts] Preprocess each dataset. 4. [2 pts] Divide each dataset into training and testing. 5. [12 pts] Build two regression models. 6. [4 pts] Test the models and compute their accuracy. Part C: Classification – 6% 1. [2 pts] Find one or two datasets in kaggle or any other source. Make sure that each dataset is at least one 500MB. 2. [2 pts] Write a detailed description of each dataset. 3. [6 pts] Preprocess each dataset. 4. [2 pts] Divide each dataset into training and testing. 5. [12 pts] Build two classification models. 6. [4 pts] Test the models and compute their accuracy. Deliverables: • One pdf file which contains: o [-2 pt] A cover page with: ▪ Project title ▪ Students’ names and IDS ▪ date of submission o The solution of each of the above questions. ▪ code ▪ output o [-1 pt] The name of your pdf file must be StudentID.pdf (ID of the student who submitted the file).