decision-tree learning technique
Cancer Classification using Self Adaptive Learning and Optimal Feature Selection in SVM
... and decision tree based techniques are used for the classification ...classification technique build with kernal ...non-linear decision using linear ...(ANN) technique performs the data ...
6
Effective Decision Tree Learning
... analysis technique. The decision tree is one of the most popular classification algorithms in current use for data mining because it is more ...Traditional decision tree classifiers are ...
6
Study of Factors Analysis Affecting Academic Achievement of Undergraduate Students in International Program
... (Decision Tree and Bayesian Network) to predict students GPA at the end of the third year of undergraduate studies and at the end of the first year of postgraduate from two different ...the Decision ...
5
Issues in Optimization of Decision Tree Learning: A Survey
... filter technique proposed is voting filter removes outlier if all or majority of classifiers misclassify the ...last technique is boosting filters in this method Adaboost is used and after n number of ...
18
An Enhanced Decision Tree Ensemble Technique For Obesity Prediction
... machine learning approaches in mobile ...machine learning algorithms namely Enhanced Decision Tree, Naïve Bayes and Support Vector Machine (Radial ...
6
Intrusion Detection Using Decision Tree Based Data Mining Technique
... C5 decision tree achieves higher classification rate accuracy, using feature selection by Gain Ratio, and less false alarm rate than MLP and naïve ...machine learning techniques (C5, MLP and Naïve ...
7
Predictive Maintenance and Monitoring of Industrial Machine using Machine Learning
... Machine learning is one of the break-through technologies of the modern digital ...machine learning techniques is used for prediction of accuracy of running production ...machine learning ...
6
Analysis Of Weka Data Mining Algorithm Reptree, Simple Cart And Randomtree For Classification Of Indian News
... classification technique that generates the binary decision ...binary tree, it generates only two ...(CART) decision tree is a learning technique, which gives the results ...
9
Object Oriented Intelligent Multi-Agent System Data Cleaning Architecture To Clean Email Data
... situation. Learning characteristics of an agent is done by verifying its previous experience from its ...with learning (MAS- L) ...and learning properties of software ...the Decision ...
14
Decision Tree Algorithms for Diagnosis of Cardiac Disease Treatment
... database. Decision tree learning algorithm has been successfully used in expert systems in finding the ...building decision tree, such as ID3, ...for decision making tree ...
7
Uncertain Data Mining using Decision Tree and Bagging Technique
... computer learning techniques to automatically analyze and extract knowledge from data in large databases Knowledge gained from data mining is in the form of model or generalization of ...summaries, decision ...
5
Prediction of Heart Disease using Decision Tree a Data Mining Technique
... Discretization is the process of converting continuous valued variables to discrete values where limited numbers of labels are used to represent the original variables. The discrete values can have a limited number of ...
8
Detection of Intrusion Using Decision Tree Based Data Mining Technique
... method i.e. J48 decision tree algorithm. The depictions of these philosophies are portrayed beneath. 4.1 WEKA , WEKA is an innovatory apparatus in the historical backdrop of the data mining and machine ...
7
Predicting and Analysis of Student Performance Using Decision Tree Technique
... classification technique such as decision ...their learning process, and the taking of timely decisions in order to prevent academic risk and ...
10
Decision Tree: A Machine Learning for Intrusion Detection
... Both Bajaj and Arora discussed in their research paper [3] the different distinctive selection methods such as information gain, gain ratio, and correlation-based feature selection, where they selected 33 features out of ...
5
On the utilization of deep and ensemble learning to detect milk adulteration
... This technique produced spectral data from the milk samples composition, which were used for training different machine learning algorithms, such as deep and ensemble decision tree ...deep ...
13
Cramers V Test Discretization Based Spatial Decision Tree Learning for Land Cover Classification
... Given learning samples from a raster data set for spatial data mining, spatial decision tree learning models is used to estimate the decision tree classifier that minimizes ...
8
A Comparative Study Of Multi-Relational Decision Tree Learning Algorithm
... major technique to develop models through machine learning algorithm and Logic Programming which works as programming paradigm which uses first order logic to represent ...other learning approaches, ...
5
A Framework for Child Development analysis and Learning Disability Prediction using a Hybrid Naive Bayes and Decision Tree Fusion Technique – NB Tree
... child's learning behavior and skills using machine learning ...predict learning disbility found in children. The purpose of learning disability prediction is to determine a child's strengths ...
7
A Survey Paper on Phishing Attacks with New Unsupervised Learning Model
... Regression Technique) is one of the popular methods of building decision tree in the machine learning ...binary decision tree by splitting the records to each node, according to ...
9