Car Acceptability Classification

Developed a machine learning model to predict car acceptability using the UCI Car Evaluation Dataset. The project compares a Multilayer Perceptron (MLP) neural network with a Support Vector Machine (SVM) for multi-class classification. After applying ordinal encoding and handling class imbalance, the MLP achieved 95% accuracy, outperforming the SVM baseline