Weka
A collection of machine learning algorithms and data analysis tools for data preprocessing, modeling, and visualization
&
| + | Comprehensive Algorithms | Offers a wide array of algorithms for data analysis and predictive modeling. |
|---|---|---|
| + | User-Friendly | Easy-to-use graphical user interface |
| + | Extensible | The user can customize and extend its functionality to suit your needs. |
| + | Data Preprocessing | Clean, transform, and prepare data for analysis. |
| + | Classification | Train models to label data into predefined classes. |
| + | Regression | Predict numeric values using regression models. |
| + | Clustering | Group similar data points together. |
| + | Feature Selection | Identify relevant features for better model performance. |
| + | Visualization Tools | Explore data patterns visually. |
| + | SQL Database Connectivity | Access SQL databases for seamless integration. |
| + | Flat File Format (ARFF) | Standardized input format for data points |
| + | Workflow Management | Allows building workflows to automate data processing and model building |
| + | Evaluation Tools | Provides metrics and techniques to assess the performance of machine learning models |
| + | Experiment Comparison | Allows you to compare and analyze the results of different models applied to the same data |
| - | Scalability | May not excel in handling exceptionally large datasets or distributed computing scenarios. |
System Requirements
Version ↓
| # | Minimum | Recommended |
|---|---|---|
| 1 | Java v8 | If you are using Windows and your computer has a display with high pixel density (HiDPI), you may need to use Java 9 or later |
| # | Minimum |
|---|---|
| 1 | Java 1.4 |
| # | Minimum |
|---|---|
| 1 | Java 5 |
| # | Minimum |
|---|---|
| 1 | Java 6 |
| # | Minimum |
|---|---|
| 1 | Java 7 |
Developer
Eibe Frank, Mark Hall, Peter Reutemann, Len Trigg, University of Waikato
Written in
Java
Initial Release
1 May 2000
Repository
Categories
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Data Mining
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Deep Learning
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