run code of prediction and review the report
Budget: $30 – $250 USD
review the prediction code and make sure it is run correctly and the result is correct
check the dataset is correct: A questionnaire collects the datasets to be used in this research.
1- check the Pre-processing and confirms it is correct
2- to check the Learning Models
3- Feature selection techniques like ANOVA, Lasso, Chi-Square, Mutual Information, and Pearson are used to identify the best features out of 37 and compared the performance between models that are built based on top features.
4-Parameter sensitivity
5-Parameters Setup
6-Evaluation
7-Classifier Performance Metrics
8-Data Mining Experiments
9-Prediction Using All Attributes and selected attributes Split the Dataset and cross-validation
10- clustering
check the dataset is correct: A questionnaire collects the datasets to be used in this research.
1- check the Pre-processing and confirms it is correct
2- to check the Learning Models
3- Feature selection techniques like ANOVA, Lasso, Chi-Square, Mutual Information, and Pearson are used to identify the best features out of 37 and compared the performance between models that are built based on top features.
4-Parameter sensitivity
5-Parameters Setup
6-Evaluation
7-Classifier Performance Metrics
8-Data Mining Experiments
9-Prediction Using All Attributes and selected attributes Split the Dataset and cross-validation
10- clustering