This repository contains my solution for the Spaceship Titanic Kaggle competition.
I implemented a Kernel SVM classifier to predict whether passengers were transported to another dimension.

• The dataset consists of information about spaceship passengers, including features like age, spending, cabin type, etc.
• The goal is to predict the Transported column (True/False).

1. Data Preprocessing:

   • Handled missing values.
   • Encoded categorical variables.
   • Scaled numerical features.

2. Model Selection:

   • Used Kernel SVM with the RBF kernel.
   • Evaluated performance using accuracy.

3. Predictions:

   • Stored final predictions in predictions_KernelSVMClassification.csv.

• KernelSVMClassification_spaceship.ipynb → Jupyter notebook with code & analysis.
• predictions_KernelSVMClassification.csv → Final submission file.
• requirements.txt → Required Python libraries.

To install required libraries, run:

pip install -r requirements.txt

Clone the repository and run the notebook:

git clone https://github.com/yourusername/Spaceship-Titanic-KernelSVM.git
cd Spaceship-Titanic-KernelSVM
jupyter notebook KernelSVMClassification_spaceship.ipynb

• Model accuracy: (0.79284)
• Kaggle leaderboard score: (880)