tree based classification model
Cramers V Test Discretization Based Spatial Decision Tree Learning for Land Cover Classification
... training based spatial learning includes two sub-routines (Node-Split and Focal ...minimum tree node size, or all the class labels are identical, a leaf labeled with the majority class will be ...a ...
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Using DRG to analyze hospital production: a re-classification model based on a linear tree-network topology
... informative classification system helps both managers and physicians evaluate the productivity of hospital departments and recognize where such productivity could be ...ideal classification system, for ...
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Decision tree classification model for land use and land cover mapping a case study
... Decision tree classifier, a machine learning algorithm, is a knowledge based data mining ...the classification and discards the remaining features at that transitional stage, thereby increasing the ...
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A hybrid classification model employing genetic algorithm and root guided decision tree for improved categorization of data
... data based on some similarity measure. Classification techniques fall under the supervised learning technique and has been widely used for the purpose of data ...First Tree (BFT) [5], ...
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A PARALLEL SCHEDULING SEQUENCE OF GF (P) EDWARDS COORDINATES COMPUTATION FOR ECC
... paper, classification of brainwave using real world data from Parkinson’s patients is ...Emotional model is produced from the classification of ...“best” classification for the emotional ...
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Classification Prediction Model Research based on Decision Tree and Application in Thrombolysis Treatment Options
... decision tree sample set attribute ...age classification, which is people are classified by ages into three categories: 18-39 years old , 40-59 years old, over 60 years ...
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Diabetes Diagnosis using Machine Learning Algorithms
... on classification of ...a classification model for diabetes using decision tree, Naïve Bayes, Support vector machine and k nearest neighbour ...The classification model is ...
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Performance Analysis on Uncertain Data using Decision Tree
... decision tree algorithms and concluded that C4.5 decision tree algorithm has a much better performance than the other two techniques based on their researches ...Decision tree is a simple and ...
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Zebrafish Larvae Classification based on Decision Tree Model: A Comparative Analysis
... segmentation, classification system for zebrafish eggs using two ways for feature extraction and also a ...the Classification And Regression Tree (CART) classifier are proposed, analysed, and ...
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A Hybrid Classification Model For Diabetes Dataset Using Decision Tree
... decision tree classification models for the pima Indians diabetes dataset and shows the tree structure formed enabling users to take accurate decisions based on the input ...FB tree is ...
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Binary Classification for Hydraulic Fracturing Operations in Oil & GasWells via Tree Based Logistic RBF Networks
... our model is a novel approach it is open for improvement in different ...our model on n < p classification problems and obtained promising ...our model on classification problems ...
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Marathi/Hindi to English Transliteration of Named Entity using WEKA Tool
... transliteration model out of three is based on multiclass classification for which j48 decision tree classifier of WEKA was used for ...
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An Efficient Decision Tree Model for Classification of Attacks with Feature Selection
... validity based reduction method (FVBRM) applied on one of the efficient classifier Naive Bayes on reduced data set with 24 features for intrusion ...case based feature selection (CFS), gain ratio (GR), info ...
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A Study on the Impact of Tensile Fabric Structure in Semi-Outdoor Spaces of Tropical Cities
... classes. Classification is an important problem in data ...records, classification decides to which class a particular record ...Decision tree is a classification scheme, which is a best and ...
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An Approach Towards E-Learning Using SVM Classification Technique and Ranking Technique in Microblog Supported Classroom: A Survey
... Data classification is a two-step process from which first step is to built describing a predetermined set of data ...a classification algorithm builds the classifier by analysing or learning from a ...
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Comparative Analysis of Classification Techniques in Data Mining Using Different Datasets
... mining, classification and prediction, and ...these classification techniques are supervised learning techniques to classify data item into predefined class ...construct classification models from an ...
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Tree based Threshold Model for Non stationary Extremes with Application to the Air Pollution Index Data
... Statistical model for high level of API is important for the purpose of forecasting the level of API so that the public can be ...covariate model in the GPD parameters for data above the threshold to ...
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A Detailed Analysis on Windows Event Log Viewer for Faster Root Cause Detection of Defect using Different Graph Plotting Method
... the model trained is not suitable for real world ...the model needs to be trained rigorously with the help of Machine ...defect based on previous ...
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A Decision-Tree-Based Algorithm for Speech/Music Classification and Segmentation
... thresholds, based on the probability density functions of the ...initial classification is performed for each segment of the audio signal, using a three-stage sieve-like approach, applying both Bayesian and ...
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A Comprehensive Review on Air Pollution Detection using Data Minging Techniques
... levels based on a dataset consisting of observations of weather and traffic variables recorded at a busy roadside in Hangzhou, ...China. Based upon the thorough examination of over twenty five classifiers ...
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