[PDF] Top 20 Diabetes Prediction using Linear Regression, Decision Tree & Least Square Support Vector Machine
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Diabetes Prediction using Linear Regression, Decision Tree & Least Square Support Vector Machine
... Diabetes mellitus (DM) be an unrelenting ailment, within which individual have elevated glucose measures. Which consequently, influences the capacity of human body to utilize optimum vitality found in sustenance ... See full document
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Weather Prediction using Linear Regression & Support Vector Machine vide Big Data
... essentially machine learning strategies, generally neural systems while some drew on probabilistic models, for example, Bayesian ...on machine learning for climate expectation we inspected, two of them ... See full document
10
Performance Evaluation of Machine Learning Approaches for Credit Scoring
... scoring. Linear Discriminant Analysis (LDA) and Logistic Regression (LR) are the statistical techniques selected and Decision Tree (DT), Support Vector Machine (SVM), ... See full document
6
Research on the Geological Sourcing of Raohe Honey by Inductively Coupled Plasma Mass Spectrometry with Primary Composite Analysis and Forecasting Models
... hierarchy tree, SOM, QT cluster analysis and 5 different classifying forecasting ...partial least squares regression (PLSR), artificial neural network (ANN), ...the Decision Tree, Naïve ... See full document
12
Particle swarm optimized partial least square support vector regression model for tax revenue prediction
... of support vector regression(SVR) construct the optimal regression function through risk minimization principle to transform the problem into solving a convex quadratic programming ...by ... See full document
9
Comparative Study On Effort Estimation Using Different Data Mining Techniques
... like Least-squares multiple linear regression and Neural Network ...Network, Regression Tree, Regression Analysis, Decision Tree, Random Forest, Logistic ... See full document
6
Sales Forecasting using Linear Regression and Support Vector Machine
... executing machine learning models that run automatically and present a monthly or quarterly forecast of a customer's sales metric ...forecasting using SVM Support Vector Machine (SVM ... See full document
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IJCSMC, Vol. 6, Issue. 8, August 2017, pg.49 – 54 A COMPARATIVE STUDY OF DIAGNOSING LIVER DISORDER DISEASE USING CLASSIFICATION ALGORITHM
... of support vector machine is to find the accurate classification technique to differentiate between members of the two classes in the training ...In support vector machine ... See full document
6
Ground Ozone Level Prediction Using Machine Learning
... and machine learning models, where polluted ozone day has class 1 and non-ozone day has class ...different machine learning models are used in the prediction of ground ozone level and their fi- nal ... See full document
9
Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model
... In this study, we did not adopt a pre-processing technique for input data for developing the respective drought models. One criticism of data-driven models without a pre-processing technique is their inability to account ... See full document
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Prediction of humidity in weather using logistic regression, decision tree, nearest neighbours, naive bayesian, support vector machine and random forest classifiers
... Humidity prediction is mainly concerned with the prediction of weather condition for a given ...The prediction of weather condition is essential for various purposes like climate monitoring, drought ... See full document
16
Crime Patterns and Prediction: A Data Mining and Machine Learning Approach
... dataset using various regression algorithms like Support Vector Machine, Decision tree regression, Random Forest ... See full document
7
Diabetes Diagnosis using Machine Learning Algorithms
... This project presented a comparison of Naïve Bayes classifier with other linear classifiers such as Logistic Regression, Support Vector Machines and K-Nearest Neighbours. Overall Naïve Bayes ... See full document
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Advanced Probabilistic Binary Decision Tree Using SVM for large class problem
... For the readers’ convenience, introduce the SVM briefly in section II. A brief introduction about the several widely used multiclass methods to divide the k classes in to binary class is in section III. The structure of ... See full document
5
Phishing Website Classification using Least Square Twin Support Vector Machine
... It is important that these website features must contain enough information to make accurate prediction. A number of traditional methodologies are utilized to categorize the phishing website, these methodology are ... See full document
6
A Machine Learning Approach to Forecast Bitcoin Prices
... A Radial Basis Function SVM Kernel is used in the project to train the input features to achieve better predictive estimation of the Bitcoin Market Price. The Kernel hyperparameters such as C, gamma and epsilon are set ... See full document
8
A Meta-Stacked Software Bug Prognosticator Classifier
... The first contribution of our work is to find the set of priority attributes that affect the cost of bug estimation the most. Second is to evaluate the stacked classifiers (Regression, Neural Network, ... See full document
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IJCSMC, Vol. 5, Issue. 5, May 2016, pg.483 – 488 A Survey on Classification Techniques in Data Mining for Analyzing Liver Disease Disorder
... Bayes, Decision Tree, Support Vector Machine, Back Propagation Neural Network and Classification and Regression Tree ... See full document
6
Analysis of various Machine Learning Techniques to Detect Phishing Email
... for machine learning. In these experiments, the two class boosted decision tree and the two class support vector machine (SVM) were used as spam ...The decision ... See full document
9
Comparison Of Datamining Techniques For Prediction Of Breast Cancer
... shows support vector machine as the best algorithm with an accuracy of about ...the prediction accuracy and including all other irrelevant features could lead to false ...for prediction ... See full document
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