[PDF] Top 20 Hombres que ejercen violencia hacia la (ex) pareja mujer: cambios y tensiones.
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A Random Forest Classifier based on Genetic Algorithm for Cardiovascular Diseases Diagnosis (RESEARCH NOTE)
... as cardiovascular disease dataset is a significant issue in pattern recognition ...individual classifier. In this work, a hybrid classification system for diagnosis of cardiovascular disease ... See full document
6
Diagnosis of Acute Myocardial Infarction using Random Forest classifier through SPECT
... related diseases, i.e cardiovascular diseases are considered as one of the primary cause of mortality in India along affecting rural and urban people of the ...country. Cardiovascular disease ... See full document
5
Usage of Data Mining Techniques in Predicting the Heart Diseases Decision Tree & Random Forest Algorithm
... heart diseases most of the papers have implemented several data mining techniques such as Naïve Bayes, Neural network, Kernel density, automatically defined groups, bagging algorithm and support vector ... See full document
18
Usage Of Random Forest Ensemble Classifier Based Imputation And Its Potential In The Diagnosis Of Alzheimer’s Disease
... single classifier alone ...yields Random Forest (RF) ensemble model that improves the overall performance by de-correlating the prediction of each ...of classifier that learns decision trees ... See full document
9
PREDICTION OF CORONARY ARTERY DISEASE USING GENETIC ALGORITHM BASED FEATURE SELECTION AND RANDOM FOREST CLASSIFIER
... The main objective of our work is to diagnose CAD with reduced number of attributes. Fourteen attributes are involved in predicting heart disease. But these attributes are reduced to seven attributes by using ... See full document
6
Recognition of Gender using Gait Energy Image Projections Based on Random Forest Classifier
... silhouette based method utilises the silhouettes of gait sequence characteristics because of their low computational complexity and noise ...picture. Based on the biological features of a person, biometric ... See full document
19
PFP RFSM: Protein fold prediction by using random forests and sequence motifs
... utilizes random forest classifier [23] and employs an extensive set of features, which incorporating sequence-based features, ...features based on BLAST. We also designed a method for ... See full document
63
Vol 8, No 2 (2016)
... classification algorithm best suits for which classification ...classification algorithm, authors applied four classification algorithms which are support vector machine (SVM), decision tree (J48) (DT), ... See full document
87
Text Analysis and Automatic Triage of Posts in a Mental Health Forum
... Table 2: The average 4-ways classification accuracies in 10xFold cross-validation for the random forest and support vec- tor machine classifiers tuned for the best parameters on two different sets of ... See full document
101
Air Pollution Prediction via Differential Evolution Strategies with Random Forest Method
... labelled forest. Random forest is one of the most successful ensemble learning techniques which have been proven to be very popular and powerful techniques in the pattern recognition and machine ... See full document
140
A support vector machine and a random forest classifier indicates a 15-miRNA set related to osteosarcoma recurrence
... This study proposes a 15-miRNAs-based SVM classifier as a potential useful tool to predict osteosarcoma recurrence. The hsa-miR-10b, hsa-miR-1227, hsa-miR-146b-3p, and hsa-miR-873 miRNAs were closely ... See full document
12
Personal Health Assistant
... sector, diagnosis of a disease is done on the basis of symptoms that are visible in ...self diagnosis for the symptoms visible to them. Sometimes search based self diagnosis may outcome with ... See full document
40
Machine learning based detection of Kepler objects of interest
... the random forest approach comprises the construction of many “simple” decision trees in the training stage and the majority vote (mode) across them in the classification ...stage random forests ... See full document
5
Detecting Lower Back Pain Using Stacked Ensemble Approach
... is based on the availability of data, which is used to train the machine to perform the desired ...output based on some features of the inputs themselves, for example, to perform image ... See full document
7
Performance Evaluation of Credit Card Fraud Transactions using Boosting Algorithms
... Abstract – In the era of digital world, internet has reached a global connectivity. The whole world has transformed into digital now. All the firms whether it is educational organizations, governmental organizations, ... See full document
24
Pixel Based Sar Image Classification using Random Forest Algorithm
... and Random Forest (RF) algorithms. For the Random Forest, a general model for classification of Remotely Sensed Radar dual-polarization data based on RF is implemented and classified of ... See full document
8
Big Data Analysis Based on Machine Learning Techniques
... Bayesian Classifier and the Support Vector Machine ...the classifier models. The classifier models used in this implementation work are Bayesian and Support Vector Machines ...the random ... See full document
55
BERMP: a cross-species classifier for predicting m6A sites by integrating a deep learning algorithm and a random forest approach
... Three developed classifiers (i.e. pRNAm-PC, M6A-HPCS and RAM-NPPS) were selected to compare with BERMP for Saccharomyces cerevisiae. All of them were based on the same dataset that contained 1307 positives and ... See full document
9
Prediction of Fine Grained Air Quality for Pollution Control
... deadly diseases which could occur when it penetrates into human ...location based on data from scant air monitoring stations, and also tries to identify the locations in which air quality monitoring ... See full document
21
Speaker Independent and text Independent Emotion Recognition System Based on Random Forest Classifier
... ABSTRACT: Recently, attention of the emotional speech signals research has been boosted in human machine interfaces due to availability of high computation capability. There are many systems proposed in the literature to ... See full document
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