[PDF] Top 20 Propuesta de contenidos para la enseñanza de la gestión de calidad de la información
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Evaluating the High Risk Groups for Suicide: A Comparison of Logistic Regression, Support Vector Machine, Decision Tree and Artificial Neural Network
... fatal suicide, which is a binary variable; using several risk factors, several classification methods were ...fatal/non-fatal suicide were included in classification ... See full document
129
Evaluation and Comparison of Different Machine Learning Methods to Predict Outcome of Tuberculosis Treatment Course
... and support as an element of the “global plan to stop TB” was considered by the World Health ...compared machine learning techniques initially to predict the outcome of TB ...including decision ... See full document
199
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 accuracy ... See full document
19
Classification Techniques for Predicting Graduate Employability
... algorithms, Decision Tree, Support Vector Machines and Artificial Neural Networks are used and being compared for the best ...show decision tree J48 produces higher ... See full document
10
Fundamental Factor Models Using Machine Learning
... DOI: 10.4236/jmf.2018.81009 115 Journal of Mathematical Finance Therefore, the following verification is carried out. First, sort the future return on equity required as a result of applying the machine learning ... See full document
106
Baseline Assisted Classification of Heart Rate Variability
... While heart rate defines the number of beats per minute, heart rate variability (HRV) quantifies the variation in time between consecutive heartbeats and is measured based on R-R interval time series as it is the time ... See full document
28
Technical Methods and Algorithms for Developing Efficient Optical Character Recognition System: An Overview
... The image is converted into eight by fifteen bitmap. Template matching systems were developed as a result to the issue of object recognition, and they contain at least completely the idea of identity comparison. ... See full document
69
Comparison Of Datamining Techniques For Prediction Of Breast Cancer
... As observed in the next part, same algorithms which were directly applied without any feature selection are shown. Result in this part evaluated shows support vector machine as the best algorithm ... See full document
5
Automatic Detection of Whitefly Pest using Statistical Feature Extraction and Image Classification Methods
... The principal objective of pre-processing is to perform some basic tasks on a given image so that the resultant image is more suitable than the original image for subsequent image processing methods like segmentation, ... See full document
8
Performance Evaluation of Machine Learning Approaches for Credit Scoring
... credit risk is imperative. Statistical techniques as well as the AI (Artificial Intelligence) techniques are chosen in this paper to assess the level of credit ...and Logistic Regression (LR) ... See full document
369
Performance Evaluation of Various Classification Algorithms
... © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 3878 classification aspect. In order to classify data, it makes use of hyperplanes which act like decision boundaries between the ... See full document
49
Supervised Learning Classification Algorithms Comparison
... supervised machine learning, classification tasks are one of the most important tasks as a part of data ...different machine learning ...are Logistic Regression, K-Nearest Neighbor, ... See full document
47
Fraud detection models and payment transactions analysis using machine learning
... In other words, we want to display a reflection on which this data hints; the cost function is connected to the discrepancy between our reflection and the data, and it implicitly contains a priori knowledge of the ... See full document
104
Comparing Three Data Mining Algorithms for Identifying the Associated Risk Factors of Type 2 Diabetes
... diabetes risk, showing that hs-CRP is an important and a common factor in three models for determining the individuals with type 2 diabetes A major strength of the present study is that it was performed in a large ... See full document
18
Online Full Text
... Abstract—Reliability-based design optimization (RBDO) is to find the optimal structural design with minimum cost subject to the required level of reliability. Since the target failure probability is usually small, ... See full document
76
Analysis of various Machine Learning Techniques to Detect Phishing Email
... of machine realizing, that can separate the follow into groups of traffic where each bunch has different traffic ...mill groups incorporate mass exchange, single and various exchanges and intelligent ... See full document
14
IJCSMC, Vol. 6, Issue. 8, August 2017, pg.49 – 54 A COMPARATIVE STUDY OF DIAGNOSING LIVER DISORDER DISEASE USING CLASSIFICATION ALGORITHM
... the network to compute and then the error is ...the neural networks learns the training ...important neural network algorithms is back propagation algorithm; this algorithm is stopped when the ... See full document
17
Machine learning and statistical approaches to classification – a case study
... a decision tree involves partitioning the training examples in a recursive (divide-and-conquer) manner to reach a ...of tree construction, some heuristics, called attribute selection measures ... See full document
82
Disease Identification in Cotton Plants Using Spatial FCM & PNN Classifier
... Santanu &Jaya described a software prototype system in paper for disease detection based on the infected images of various rice plants. They used image growing, image segmentation techniques to detect infected parts ... See full document
14
Comparing different supervised machine learning algorithms for disease prediction
... supervised machine learning algorithms to make a comparison among them for disease ...performance comparison between least-square and sparse SVMs; instead of considering them under the SVM ... See full document
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