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KNN Classifier and K-Means Clustering for Robust Classification of Epilepsy from EEG Signals. A Detailed Analysis

Knn Classifier and K-Means Clustering Fo;...

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Fuzzy Clustering Via Proportional Membership Model

), modelling a typological classification. In fuzzy clustering, the fuzzy c-means (FCM) method has become one of the most popular techniques. As a;

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Risk Classification by Means of Clustering

Determining risk-adequate insurance premiums is a core issue in actuarial mathematics. This study is specifically concerned with;

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Advanced Analysis and Learning on Temporal Data

and embeddings for time series classification, clustering or for dimensionality reduction. The second part presents approaches on;

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Lecture Notes In Data Mining

(classification, clustering and association rules) by offering overviews that include both analysis and insight.The initial chapters lay a framework;

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Machine Intelligence: Recent Advances

preserving data mining, as well as an authentication mechanism using fingerprint classification. Section V contains an extension of open source iCub;

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Mixture Model-Based Classification

This is a great overview of the field of model-based clustering and classification by one of its leading developers. McNicholas provides a;

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Mixture Model-Based Classification

This is a great overview of the field of model-based clustering and classification by one of its leading developers. McNicholas provides a;

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Apache Mahout Clustering Designs

is a hand's-on guide with examples using real-world datasets. Each chapter begins by explaining the algorithm in detail and follows up with;

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Advances in Knowledge Discovery and Data Mining

from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy;

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Advances in Knowledge Discovery and Data Mining

from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy;

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Fuzzy Approach to Hierarchical Clustering

search of Tolerance coefficient for Definite hierarchical agglomerative clustering method and to find Partition optimality coefficient by means;

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Time Series Clustering and Classification

clustering and classifying different types of large datasets, including time series data. Time Series Clustering and Classification includes relevant;

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Time Series Clustering and Classification

clustering and classifying different types of large datasets, including time series data. Time Series Clustering and Classification includes;

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Model-Based Clustering and Classification for Data Science

clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously;

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Fuzzy Sets & their Application to Clustering & Training

clustering applications. It provides a unified mathematical framework for fuzzy classification and clustering, a methodology for developing training;

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Graph-theoretic Techniques For Web Content Mining

clustering and k-nearest neighbors classification, can be easily extended to work with graphs instead of vectors. This allows for the utilization;

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Data Science

Federation of Classification Societies (IFCS2015), which was hosted by the Alma Mater Studiorum, University of Bologna, from July 5 to 8, 2015.;

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Clustering Methodology for Symbolic Data

in order to extract knowledge from such a data. Classification Methodology for Symbolic Data: * Provides new classification methodologies for;

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Unsupervised Machine Learning for Clustering in Political and Social Research

In the age of data-driven problem-solving, applying sophisticated computational tools for explaining;...

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Fuzzy Sets, Rough Sets, Multisets and Clustering

together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as;

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Data Clustering

on cluster analysis, including the classification of data and the corresponding similarity measures, followed by the presentation of over 50;

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Classification

develop better and more efficient ways to summarize and extract information from these large, multivariate data sets. The field of classification;

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Classification

develop better and more efficient ways to summarize and extract information from these large, multivariate data sets. The field of classification;

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Satellite Image Analysis Clustering and Classification

information. Highly accurate automatic classification and decision support systems can facilitate the efforts of data analysts, reduce human error;

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Clustering

Often considered more of an art than a science, books on clustering have been dominated by learning through example with techniques chosen;

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Clustering

Often considered more of an art than a science, books on clustering have been dominated by learning through example with techniques chosen;

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