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Massive On-line Analysis is an environment for massive data mining. MOA provides a framework for data stream mining and includes tools for evaluation and a collection of machine learning algorithms. Related to the WEKA project, also written in Java, while scaling to more demanding problems.

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/*
 *    AbstractCBase.java
 *    Copyright (C) 2013 Aristotle University of Thessaloniki, Greece
 *    @author D. Georgiadis, A. Gounaris, A. Papadopoulos, K. Tsichlas, Y. Manolopoulos
 *
 *
 *    Licensed under the Apache License, Version 2.0 (the "License");
 *    you may not use this file except in compliance with the License.
 *    You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 *    Unless required by applicable law or agreed to in writing, software
 *    distributed under the License is distributed on an "AS IS" BASIS,
 *    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *    See the License for the specific language governing permissions and
 *    limitations under the License.
 *    
 *    
 */

package moa.clusterers.outliers.AbstractC;

import java.util.ArrayList;
import java.util.Vector;
import moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode;
import moa.clusterers.outliers.MyBaseOutlierDetector;

public abstract class AbstractCBase extends MyBaseOutlierDetector {    
    protected static final Long FIRST_OBJ_ID = 1L;
    
    // object identifier increments with each new data stream object
    protected Long objId;
    // list used to find expired nodes
    protected Vector windowNodes; 
    protected ISBIndex ISB;
    protected int m_WindowSize;
    protected double m_radius;
    protected double m_Fraction;
    protected boolean bWarning = false;
    
    // statistics
    public int m_nBothInlierOutlier;
    public int m_nOnlyInlier;
    public int m_nOnlyOutlier;
    
    @Override
    public String getObjectInfo(Object obj) {
        if (obj == null) return null;
        
        ISBNode node = (ISBNode) obj;
        
        ArrayList infoTitle = new ArrayList();
        ArrayList infoValue = new ArrayList();
        StringBuilder sb = new StringBuilder();

        // show node position
        for (int i = 0; i < node.obj.dimensions(); i++) {
            infoTitle.add("Dim" + (i+1));
            infoValue.add(String.format("%.3f", node.obj.get(i)));
        }
        
        // show node properties
        infoTitle.add("id");
        infoValue.add(String.format("%d", node.id));
        
        sb.append("");
        sb.append("");
        int i = 0;
        while(i < infoTitle.size() && i < infoValue.size()){
            sb.append("");
            i++;
        }
        sb.append("
"+infoTitle.get(i)+":"+infoValue.get(i)+"
"); sb.append(""); return sb.toString(); } @Override public String getStatistics() { StringBuilder sb = new StringBuilder(); sb.append("Statistics:\n\n"); // get counters of expired nodes int nBothInlierOutlier = m_nBothInlierOutlier; int nOnlyInlier = m_nOnlyInlier; int nOnlyOutlier = m_nOnlyOutlier; // add counters of non expired nodes for (ISBNode node : windowNodes) { if ((node.nInlier > 0) && (node.nOutlier > 0)) nBothInlierOutlier++; else if (node.nInlier > 0) nOnlyInlier++; else nOnlyOutlier++; } int sum = nBothInlierOutlier + nOnlyInlier + nOnlyOutlier; if (sum > 0) { sb.append(String.format(" Nodes always inlier: %d (%.1f%%)\n", nOnlyInlier, (100 * nOnlyInlier) / (double)sum)); sb.append(String.format(" Nodes always outlier: %d (%.1f%%)\n", nOnlyOutlier, (100 * nOnlyOutlier) / (double)sum)); sb.append(String.format(" Nodes both inlier and outlier: %d (%.1f%%)\n", nBothInlierOutlier, (100 * nBothInlierOutlier) / (double)sum)); sb.append(" (Sum: " + sum + ")\n"); } sb.append("\n Total range queries: " + nRangeQueriesExecuted + "\n"); sb.append(" Max memory usage: " + iMaxMemUsage + " MB\n"); sb.append(" Total process time: " + String.format("%.2f ms", nTotalRunTime / 1000.0) + "\n"); return sb.toString(); } Long GetWindowEnd() { return objId - 1; } Long GetWindowStart() { Long x = GetWindowEnd() - m_WindowSize + 1; if (x < FIRST_OBJ_ID) x = FIRST_OBJ_ID; return x; } boolean IsWinFull() { return (GetWindowEnd() >= FIRST_OBJ_ID + m_WindowSize - 1); } Long GetExpirationTime(ISBNode node) { return node.id + m_WindowSize; } void AddNode(ISBNode node) { windowNodes.add(node); ISB.Insert(node); } void RemoveNode(ISBNode node) { windowNodes.remove(node); ISB.Remove(node); RemoveExpiredOutlier(new Outlier(node.inst, node.id, node)); // ### remove when expired? // update statistics if ((node.nInlier > 0) && (node.nOutlier > 0)) m_nBothInlierOutlier++; else if (node.nInlier > 0) m_nOnlyInlier++; else m_nOnlyOutlier++; } ISBNode GetExpiredNode() { if (windowNodes.size() <= 0) return null; // get oldest node ISBNode node = windowNodes.get(0); // check if node has expired if (node.id < GetWindowStart()) { return node; } return null; } void SaveOutlier(ISBNode node) { AddOutlier(new Outlier(node.inst, node.id, node)); node.nOutlier++; // update statistics } void RemoveOutlier(ISBNode node) { RemoveOutlier(new Outlier(node.inst, node.id, node)); node.nInlier++; // update statistics } @Override protected boolean IsNodeIdInWin(long id) { if ((GetWindowStart() <= id) && (id <= GetWindowEnd()) ) return true; else return false; } void PrintWindow() { Println("Window [" + GetWindowStart() + "-" + GetWindowEnd() + "]: "); ISBNode node; for (int i = 0; i < windowNodes.size(); i++) { node = windowNodes.get(i); Print(" Node: "); PrintNode(node); } } void PrintNode(ISBNode n) { Print("id=" + n.id + " ("); int dim = n.obj.dimensions(); for (int d = 0; d < dim; d++) { Print(Double.toString(n.obj.get(d))); if (d < dim - 1) Print(", "); } Println(")"); } public void Print_lt_cnt(ArrayList lt_cnt) { for (int i = 0; i < lt_cnt.size(); i++) { Print("(" + i + ": " + lt_cnt.get(i) + ") "); } Println(""); } }




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