Rain Prediction Using Machine Learning

Rain Prediction Using Machine Learning

Registration ID: IJNRD_180981

Published ID: IJNRD2204082

DOI: Click Here to Get

Vijithra Nair , Megha Mathew , Sweta Bhattacharjee , Arashdip Singh , Prof. Payel Thakur

ARIMA, CatBoost, Random Forest, Rainfall prediction, XgBoost

As agriculture being the key point of survival, Rainfall is the important source for its cultivation. Rainfall prediction has always been a major problem as prediction of rainfall gives awareness to people and to know in advance about rain so as to take necessary precautions to protect their crops from rain. A particular dataset is taken from Kaggle community and this project predicts whether it will rain tomorrow or not by using the rainfall in dataset. CatBoost model is implemented in this project as it is an open sourced machine learning algorithm, and features great quality without the parameter tuning, categorical feature support, improved accuracy and fast prediction. CatBoost model is a gradient boosting toolkit and two critical algorithms classical and innovative are introduced to create a fight in prediction shift present in currently existing implementations of gradient boosting algorithms. CatBoost performed very well giving an AUC (Area under curve) score 0.8 and ROC ( Receiver operating characteristic curve) score as 89. ROC is called as an evaluating curve whereas AUC presents a degree or measure of separability as the model is skilled enough to distinguish between classes. An Exploratory data analysis is done to examine data distribution, outliers and provides tools for visualizing and understanding the data through graphical representation. A dashboard is implemented to showcase the information that is represented in datasets i.e. any changes in the data will result in different types of graphs. A linear SVC (Support vector classifier) provides a best fit hyperplane that divides the data and feeds some features to the classifier to detect what the predicted class is and results in desired output.

Published Paper   E-Certificate

"Rain Prediction Using Machine Learning", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.7, Issue 4, page no.687-693, April-2022, Available :https://ijnrd.org/papers/IJNRD2204082.pdf

Volume 7 Issue 4, April-2022

Pages : 687-693

Paper Reg. ID: IJNRD_180981

Published Paper Id: IJNRD2204082

Downloads: 000121149

Research Area: Computer Engineering 

Country: Navi Mumbai/Raigarh, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2204082.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2204082

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

Indexing In Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar | AI-Powered Research Tool, Microsoft Academic, Academia.edu, arXiv.org, Research Gate, CiteSeerX, ResearcherID Thomson Reuters, Mendeley : reference manager, DocStoc, ISSUU, Scribd, and many more

How to submit the paper?

Important Dates for Current issue

Paper Submission Open For: August 2025

Current Issue: Volume 10 | Issue 8

Last Date for Paper Submission: Till 31-Aug-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: International Peer-reviewed, Refereed, and Open Access Journal.

Subject Category: Research Area