Welcome to the WekaRunner project! This Java application utilizes the Weka library for machine learning to classify patients into "Demented" or "Non-demented" categories based on MMSE scores. The project consists of a command-line interface for both analyzing datasets and making predictions for single instances.
Make sure you have the following installed on your system:
- Java (JRE or JDK)
- Weka library
To analyze a dataset and get the number of "Demented" and "Non-demented" cases. This file must include the following attributes: MMSE score and Group (that can be empty). Use the following command:
java -jar WekaAplicatie-1.0-SNAPSHOT-all.jar -f <path-to-dataset-file>
Ensure that the dataset file has a '.arff' extension.
To make predictions for a single instance based on the MMSE score, use the following command:
java -jar WekaAplicatie-1.0-SNAPSHOT-all.jar -v <MMSE-score>
Make sure to replace <MMSE-score>
with the actual MMSE score you want to predict.
-
-f, --file: Analyze a dataset. Provide the path to the dataset file.
-
-v, --value: Make predictions for a single instance. Provide the MMSE score.
java -jar WekaAplicatie-1.0-SNAPSHOT-all.jar -f DataGuess.arff
java -jar WekaAplicatie-1.0-SNAPSHOT-all.jar -v 28
- Ensure that the dataset follows the '.arff' format.
- The MMSE score must be a numeric value between 1 and 30.
Thema09DementiaPrediction.docx is the document were u will find the EDA steps of this project for cleaning the dataset.
for any reported issues or help: e.a.ooms@st.hanze.nl