# New-Micro-Cluster-Nearest-Neighbour-MC-NN-for-Real-Time-Preprocessing-Technique

**Repository Path**: wu-man/New-Micro-Cluster-Nearest-Neighbour-MC-NN-for-Real-Time-Preprocessing-Technique

## Basic Information

- **Project Name**: New-Micro-Cluster-Nearest-Neighbour-MC-NN-for-Real-Time-Preprocessing-Technique
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-04-04
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# New-Micro-Cluster-Nearest-Neighbour-MC-NN-for-Real-Time-Preprocessing-Technique
1. Download MOA Source Code

2. Create new java package (if it does not exist yet):

   MathPackages
   
   moa.classifiers
   
   moa.classifiers.MicroClusterSkipList
   
   moa.classifiers.core.driftdetection
   
   moa.classifiers.drift
   
3. Add the following java classes into the packages (2):

   (MathPackages) 
   
       NormalizeAttributes.java
       
       PercentageDifference.java
       
       StandardDeviation.java
       
   (classifiers) 
   
       MicroCluster.java
       
       MicroClusterManager.java
       
       MicroClusterManagerMedian.java
       
       MicroClusterMedian.java
       
       MicroClustersSingle.java
       
       MicroClustersSingleMedian.java
       
   (MicroClusterSkipList)
   
       FIFO_LinkedList.java
       
       Node.java
       
       SkipList.java
       
       SkipListManager.java
       
   (driftdetection)
   
       ChangeDetector.java
       
       MicroCluster_FeatureTracker_MCNN_InterquartileRange.java
       
       MicroCluster_FeatureTracker_MCNN_Variance.java
       
   (drift)
   
       DriftDetectionMethodClassifier.java
       
4. Create new java package (if it does not exist yet):

   moa.gui
   
5. Add the following java class into the package (4): 

   GUI.java
   
6. Run MOA:   

   moa.gui.GUI.java
   
7. Click on classification - Configure

8. Choose EvaluatePrequential

9. Learner: Click on Edit and choose SingleClassifierDrift: 

   baseLearner: Choose a classifier (i.e., HoeffdingTree)
   
   driftDetectionMethod: Choose the MCNN
   
      (old MCNN with Variance) MicroCluster_FeatureTracker_MCNN_Variance.java
      
      (new MCNN with IQR) MicroCluster_FeatureTracker_MCNN_InterquartileRange