Supervised Learning and Statistical Estimation

1996 ◽  
pp. 169-186
Author(s):  
Gustavo Deco ◽  
Dragan Obradovic
Keyword(s):  
Supervised Learning ◽  
Statistical Estimation

A Supervised Learning Approach for Dynamic Sampling (SLADS) in Raman Hyperspectral Imaging

2018 ◽  
Vol 2018 (15) ◽  
pp. 132-1-1323
Author(s):  
Shijie Zhang ◽  
Zhengtian Song ◽  
G. M. Dilshan P. Godaliyadda ◽  
Dong Hye Ye ◽  
Atanu Sengupta ◽  
...  
Keyword(s):  
Supervised Learning ◽  
Hyperspectral Imaging ◽  
Learning Approach ◽  
Dynamic Sampling

An IoT Device Identification Method based on Semi-supervised Learning

2020 ◽  
Author(s):  
Linna Fan ◽  
Shize Zhang ◽  
Yichao Wu ◽  
Zhiliang Wang ◽  
Chenxin Duan ◽  
...  
Keyword(s):  
Supervised Learning ◽  
Device Identification ◽  
Identification Method

DIFFRACTION ANALYSIS OF DEFORMED METALS: Theory, Methods, Programs

2019 ◽  
Author(s):  
Faina Satdarova
Keyword(s):  
Experimental Design ◽  
Dislocation Density ◽  
Mathematical Models ◽  
Diffraction Analysis ◽  
Experimental Research ◽  
Russian Federation ◽  
Statistical Estimation ◽  
X Rays ◽  
National University ◽  
The Russian Federation

General analysis of the distribution of crystals orientation and dislocation density in the polycrystalline system is presented. Recovered information in diffraction of X-rays adopting is new to structure states of polycrystal. Shear phase transformations in metals — at the macroscopic and microscopic levels — become a clear process. Visualizing the advances is produced by program included in package delivered. Mathematical models developing, experimental design, optimal statistical estimation, simulation the system under study and evolution process on loading serves as instrumentation. To reduce advanced methods to research and studies problem-oriented software will promote when installed. Automation programs passed a testing in the National University of Science and Technology “MISIS” (The Russian Federation, Moscow). You score an advantage in theoretical and experimental research in the field of physics of metals.

Pembobotan Berdasarkan Tingkat Kesamaan Semantik pada Metode Fuzzy Semi-Supervised Co-Clustering untuk Pengelompokkan Dokumen Teks

2014 ◽  
Vol 6 (2) ◽  
pp. 46-51
Author(s):  
Galang Amanda Dwi P. ◽  
Gregorius Edwadr ◽  
Agus Zainal Arifin
Keyword(s):  
Supervised Learning ◽  
Semantic Similarity ◽  
The Other ◽  
Classification Result ◽  
Document Similarity ◽  
The Matrix ◽  
Index Terms ◽  
Membership Value ◽  
Degree Of Similarity

Nowadays, a large number of information can not be reached by the reader because of the misclassification of text-based documents. The misclassified data can also make the readers obtain the wrong information. The method which is proposed by this paper is aiming to classify the documents into the correct group.  Each document will have a membership value in several different classes. The method will be used to find the degree of similarity between the two documents is the semantic similarity. In fact, there is no document that doesn’t have a relationship with the other but their relationship might be close to 0. This method calculates the similarity between two documents by taking into account the level of similarity of words and their synonyms. After all inter-document similarity values obtained, a matrix will be created. The matrix is then used as a semi-supervised factor. The output of this method is the value of the membership of each document, which must be one of the greatest membership value for each document which indicates where the documents are grouped. Classification result computed by the method shows a good value which is 90 %. Index Terms - Fuzzy co-clustering, Heuristic, Semantica Similiarity, Semi-supervised learning.

LATTE - Linking Acoustic Tests and Tagging Using Statistical Estimation

2013 ◽  
Author(s):  
Len Thomas ◽  
John Harwood ◽  
Ian L. Boyd ◽  
David Moretti
Keyword(s):  
Statistical Estimation
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