Classification is a classical problem in machine learning
and data mining. Given a set of training data tuples, each
having a class label and being represented by a feature vector,
the task is to algorithmically build a model that predicts
the class label of an unseen test tuple based on the tuple s
feature vector. One of the most popular classification models
is the decision tree model. Decisions trees are popular because
they are practical and easy to understand. Rules can also be
extracted from decision trees easily. Many algorithms ....etc

[:=Read Full Message Here=:]

future enhancement of efficient computation of range aggregates against uncertain location based queries

Abstract

In many applications, including location-based services, queries may not be precise. In this paper, we study the problem of efficiently computing range aggregates in a multidimensional space when the query location is uncertain. Specifically, for a query point Q whose location is uncertain and a set S of points in a multidimensional space, we want to calculate the aggregate (e.g., count, average and sum) over the subset S' of S su ....etc

[:=Read Full Message Here=:]

I need flow of modules and module for this project. I need a detailed description and implementation for the project ....etc

[:=Read Full Message Here=:]

what are the distributed based algorithms used in the decision ....etc

[:=Read Full Message Here=:]

import java.awt.*;
import java.awt.event.*;
import java.applet.*;

public class KeyEvents extends Applet
implements KeyListener
{
String msg = ;
int x = 10, y = 20 ;
public void init()
{
addKeyListener(this);
requestFocus();
}
public void KeyPressed(KeyEvent ke)
{
showStatus(Key Down);
int key = ke.getKeyCode();
switch(key)
{
case KeyEvent.VK_F1:
msg += ;
case KeyEvent.VK_F2:
msg += ;
case KeyEvent.VK_F3:
msg += ;
case KeyEvent.VK_PAGE_DOWN:
ms ....etc

[:=Read Full Message Here=:]

hi good morning sir.
please could you tell how to download this project report. ....etc

[:=Read Full Message Here=:]

Abstract There is a growing need for systems that react automatically to events. While some events are generated externally and deliver data across distributed systems, others need to be derived by the system itself based on available information. Event derivation is hampered by uncertainty attributed to causes such as unreliable data sources or the inability to determine with certainty whether an event has actually occurred, given available information. Two main challenges exist when designing a solution for event derivation under uncertainty ....etc

[:=Read Full Message Here=:]

INTRUSION DETECTION SYSTEM USING RULE-BASED SYSTEMS
Presented By:
S. Jeya,

Assistant Professor, Department of Computer Applications (M. C. A), K.S.R. College of Engineering, Thiruchengode.
ABSTRACT

This paper describes a technique of applying Genetic Algorithm to network Intrusion Detection Systems. A brief overview of the Intrusion Detection System, genetic algorithm, rule based system and related detection techniques is presented. As the transmission of data over the internet increases, the n ....etc

[:=Read Full Message Here=:]

ppt for efficient computation of range aggregates against uncertain location based queries..
base paper and reference for this project also..
ppt for efficient computation of range aggregates against uncertain location based queries..
base paper and reference for this project also.. ....etc

[:=Read Full Message Here=:]

Abstract

Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information. Value uncertainty arises in many applications during the data collection process. Example sources of uncertainty include measurement/quantization errors, data staleness, and multiple repeated measurements. With uncertainty, the value of a data item is often represented not by one single value, but by multiple values forming a probability distribution. Rather than abstracting unc ....etc

[:=Read Full Message Here=:]