Create a deep neural network to perform the process classification of mushrooms characteristic and using hyperparameter tuning to get the best model. Then, do analysis on accuracy, precision, recall and, f1-score of the model and also determine the features that are strongly suspected of being related with toxics of a mushroom.
- Deep Learning
- Neural Network
- Python
- Pandas
- Matplotlib
- Numpy
- Seaborn
- Keras
- Tensorflow
- Sklearn
- Dataset analysis
- Cleaning data
- Checking missing values
- Checking duplicates data
- Data Visualization
- Encoding
- Data nominal : onehot encoding
- Data binary : ordinal encoding
- Sampling data
- Feature Selection
- Using Pearson Correlation
- Data preparation
- Train-test-val split with the proportion 7.5:1.25:1.25
- Tuning hyperparameter
- Best number of layer : 3
- Best number of neuron : 50
- Build the model
- Model evaluation
- Precision : 0.99
- Recall : 0.99
- F1-score : 1.00
- Accuracy : 99%