WeatherWise ML

Comparative Analysis of Multi-linear Regression and K-Nearest Neighbor Models in Rainfall Prediction

Comparing two Supervised Machine Learning Models on its Ability to Predict Rainfall

Mission of the project

The project aims to compare two machine learning models. K-nearest Neighbor and Multi-linear regression and compare their accuracy in predicting rainfall. Once tested I will implement a web based solution to display rainfall predictions within an area.

Planning Phase

Planning Phase aimed to provide a brief overview of the proposed system and aims to implement a Front-end to allow users to interact with the model. Breaking down the layout and proposed flow of the system we can look at the following break down of the back end and front end.

Proposed Back End Implementation

The proposed breakdown and flow of the back-end and how it would interact with the front- end implementation. Once the program begins it will read the data and follow the proposed steps to train and validate the model. Implement most accurate model.

Functional Diagram of WWML

Proposed Front End Implementation

Front-end Implementation aims to utilize the data presented by the model and update by receiving predictions and displaying them for users to interact with. The proposed client is a web based solution to allow users to access it for any device.