You are expected to generate a fake Nairobi Office Price Simulated dataset of size 100 with One feature 𝒙 (office size assume a suitable distribution) and one target 𝑦 (office price also assume a suitable distribution). Write class logic for Mean Squared Error to be used as your Performance Measure Technique and Gradient Descent as your learning algorithm Set random initial values for slope (m) and y-intercept (c) and train an intelligent linear regression model of your dataset above then plot the line of best fit Use the above learnt line to predict the office price when the size is 100 sq. ft.
You are provided with the Housing Pricing dataset.
i. Prepare a dataset description file ii. Prepare the dataset for training iii. Fill in Missing Values iv. Encode the dataset v. Standardize the dataset vi. Perfom feature extraction using PCA vii. Perform feature selection using L1 viii. Train a regression model using PCA with 2 compnents
Loan Prediction
Melvin Ngure - 110497 Suzan Onyango - 111234 Shawn Ng'iela - 111882 Marysalome Omwega - 110694