Nursery Admission Prediction uses Machine Learning classification algorithms to categorize whether the candidate is priority, recommended or not recommended to be admitted.
- Support Vector Machines
- Random Forest
- Logistic Regression
- XGBoost
The dataset is Nursery Data Set.
The accuracy of prediction is displayed for each algorithm.
Label Encoder and get_dummies()
is used for converting categorical data into numeric data,
Extra Tree Classifier,SelectKBest and Chi-Square for Feature Selection
- Paste the address of the directory where your Nursery.csv file is saved
Eg.dataset = pd.read_csv(r'C:\Projects\NurseryAdmissionPrediction\Nursery.csv')
. - Install XGBoost via the command prompt.
conda install -c anaconda py-xgboost
(for Anaconda prompt)