[PDF] Top 20 A New Unsupervised Clustering based Feature Extraction Method
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A New Unsupervised Clustering based Feature Extraction Method
... in unsupervised feature extraction, where no prior knowledge about pdfs of data or about its class-distribution is ...as new irrelevant features are added ...extracting new features ... See full document
7
A new kernel method for hyperspectral image feature extraction
... precise extraction of target ...mainly based on information theory and spectral variance, such as methods based on informa- tion entropy proposed by Bajcsy and Groves (2004), mutual information to ... See full document
10
Automated spike sorting algorithm based on Laplacian eigenmaps and k means clustering
... a new automatic spike sorting method based on feature extraction by Laplacian eigenmaps combined with k-means ...proposed method was compared against previously reported ... See full document
14
Unsupervised Feature Selection for Relation Extraction
... an unsupervised re- lation extraction algorithm, which in- duces relations between entity pairs by grouping them into a “natural” num- ber of clusters based on the similarity of their ...noisy ... See full document
6
Unsupervised Anomaly Detection with Unlabeled Data Using Clustering
... environment. New intrusion types, of which detection systems are unaware, are the most difficult to ...a clustering-based intrusion detection algorithm, unsupervised anomaly detection, which ... See full document
5
An efficient clustering based texture feature extraction for medical image
... In some medical applications where a tissue of interest covers a large fraction of the image or a prior knowledge on the region of interest is available, extracting features by fixed blocs in the image is sufficient. ... See full document
7
A Feature Extraction Method Based on VMD and RDT and Its Application in Engine Crankshaft Bearing Fault
... a new fault feature extraction method for engine crankshaft bearing is proposed based on the variational mode decomposition and random decrement ...proposed method is verified by ... See full document
17
Video Copy Detection based on Uniform Local Binary Pattern
... a new video feature extraction method based on uniform LBP feature with rotation invariance and video matching algorithm based on chi-square ...complexity based on ... See full document
6
Highlights A New Advanced In silico Drug Discovery Method for Novel Coronavirus (SARS-CoV-2) with Tensor Decomposition-based Unsupervised Feature Extraction
... necessary. Method: In this study, we applied the re- cently proposed method tensor decomposition (TD)-based unsupervised feature extraction (FE) to gene expression profiles of ... See full document
18
A Novel Gesture Control Scheme of Mobile Robots Based on ROS
... segmentation method divides the skin color region from the image through the clustering feature of the skin color in the color space, and uses the feature information of skin color to ... See full document
7
Analysis of Clustering Techniques for Retrieval of Images using Proposed Feature Extraction Method
... k-means clustering to reduce the feature ...search based on scale invariant feature transform descriptors using k-means clustering ...texture feature extraction technique ... See full document
8
Evaluating Unsupervised Ensembles when applied to Word Sense Induction
... categorized based on their context model and their clustering algorithm into two categories: feature vector methods and graph ...methods. Feature vector methods simply transform each context ... See full document
6
Unsupervised Feature Extraction for Time Series Clustering Using Orthogonal Wavelet Transform
... time-series feature extrac- tion algorithm using orthogonal wavelet for automatically choosing feature dimensionality for ...the feature dimensionality is circum- vented by choosing the appropriate ... See full document
15
Feature Sampling Based Unsupervised Semantic Clustering for Real Web Multi-View Content
... large feature space and leads to the computational challenge during matrix decomposition ...algorithm based on the non-negative matrix factoriza- tion that attempts to use feature sampling strategy ... See full document
8
Unsupervised Feature Selection Using Recursive k- Means Silhouette Elimination (RkSE): A Two- Scenario Case Study for Fault Classification of High- Dimensional Sensor Data
... filter feature selection ...k-means based on feature weighting or ranking: The general idea of k-means for feature selection based on feature weighting begins with ... See full document
15
Selection of Informative Template in Hierarchical Sparse Method
... template method based on k-mean is significantly affected by these disad- ...8]. Based on this, we propose a new technique to extract compact template sets with better discrimination ...This ... See full document
8
A REVIEW ON VARIOUS TEXT MINING TECHNIQUES AND ALGORITHMS
... the method of extracting meaningful information or knowledge or patterns from the available text documents from various ...classification, clustering and information extraction are available under ... See full document
12
Unsupervised Feature Rich Clustering
... the clustering via external information, and those which cluster along multiple dimensions and then select an appropriate ...for unsupervised sentiment classification, similar to LDA, but only modeling a ... See full document
12
A new unsupervised feature selection method for text clustering based on genetic algorithms
... Feature extraction is the process of extracting new features from the set of all features by means of some functional mapping (Liu et ...on feature extraction including those in (Bao et ... See full document
16
A NEW APPROACH FOR IMAGE FEATURE VECTOR CLASSIFICATION USING UNSUPERVISED CLUSTERING METHOD
... the unsupervised classification, however an algorithm is first applied to the image and some spectral classes (also called clusters) are ...efficient method to identify and classify the exudates as hard and ... See full document
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