spritamdas / regression-with-a-flood-prediction-dataset-playground-series---season-4-episode-5-

The goal of this competition is to predict the probability of a region flooding based on various factors.

Regression-with-a-Flood-Prediction-Dataset-Playground-Series---Season-4-Episode-5-

Python files Description:
floodprobability-spritam_voting.ipynb - Using Votting Regressor and GradientBoosting,Xgboosting, Catboosting, Histboosting and as baseline models

Objective
The goal of this competition is to predict the probability of a region flooding based on various factors.

Dataset Description
The dataset for this competition (both train and test) was generated from a deep learning model trained on the Flood Prediction Factors dataset. Feature distributions are close to, but not exactly the same, as the original. Feel free to use the original dataset as part of this competition, both to explore differences as well as to see whether incorporating the original in training improves model performance.

Files
train.csv - the training dataset; FloodProbability is the target
test.csv - the test dataset; your objective is to predict the FloodProbability for each row
sample_submission.csv - a sample submission file in the correct format

Link for Files(Datasets): https://www.kaggle.com/competitions/playground-series-s4e5/data