scholarly journals Efficient algorithm for testing goodness-of-fit for classification of high dimensional data

2009 ◽  
Vol 50 ◽  
Author(s):  
Gintautas Jakimauskas
Keyword(s):  
Goodness Of Fit ◽  
Projection Pursuit ◽  
Classification Problem ◽  
Gaussian Mixture ◽  
Sequential Data ◽  
Data Partition ◽  
Computationally Efficient ◽  
Efficient Procedure ◽  
Selection Of

Let us have a sample satisfying d-dimensional Gaussian mixture model (d is supposed to be large). The problem of classification of the sample is considered. Because of large dimension it is natural to project the sample to k-dimensional (k = 1,  2, . . .) linear subspaces using projection pursuit method which gives the best selection of these subspaces. Having an estimate of the discriminant subspace we can perform classification using projected sample thus avoiding ’curse of dimensionality’.  An essential step in this method is testing goodness-of-fit of the estimated d-dimensional model assuming that distribution on the complement space is standard Gaussian. We present a simple, data-driven and computationally efficient procedure for testing goodness-of-fit. The procedure is based on well-known interpretation of testing goodness-of-fit as the classification problem, a special sequential data partition procedure, randomization and resampling, elements of sequentialtesting.Monte-Carlosimulations are used to assess the performance of the procedure.

scholarly journals A Simple Method for Testing Independence of High-Dimensional Random Vectors

2016 ◽  
Vol 37 (1) ◽  
Author(s):  
Gintautas Jakimauskas ◽  
Marijus Radavičius ◽  
Jurgis Sušinskas
Keyword(s):  
Goodness Of Fit ◽  
Classification Problem ◽  
Data Driven ◽  
Sequential Testing ◽  
High Dimensional ◽  
Computationally Efficient ◽  
Random Vectors ◽  
Simple Method ◽  
Efficient Procedure ◽  
Testing Independence

A simple, data-driven and computationally efficient procedure for testing independence of high-dimensional random vectors is proposed. The procedure is based on interpretation of testing goodness-of-fit as the classification problem, a special sequential partition procedure, elements of sequential testing, resampling and randomization. Monte Carlo simulations are carried out to assess the performance of the procedure.

scholarly journals Comparative of Machine Learning Algorithms and Datasets to Classify Natural Coverage in the Cajas National Park (Ecuador) Based on GEOBIA Approach

Proceedings ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 20
Author(s):  
Diego Pacheco Prado ◽  
Luis Ángel Ruiz
Keyword(s):  
Random Forest ◽  
National Park ◽  
Classification Problem ◽  
Machine Learning Algorithms ◽  
High Resolution Data ◽  
Natural Land ◽  
Geographic Datasets ◽  
Land Cover Maps ◽  
Selection Of

GEOBIA is an alternative to create and update land cover maps. In this work we assessed the combination of geographic datasets of the Cajas National Park (Ecuador) to detect which is the appropriate dataset-algorithm combination for the classification tasks in the Ecuadorian Andean region. The datasets included high resolution data as photogrammetric orthomosaic, DEM and derivated slope. These data were compared with free Sentinel imagery to classify natural land covers. We evaluated two aspects of the classification problem: the appropriate algorithm and the dataset combination. We evaluated SMO, C4.5 and Random Forest algorithms for the selection of attributes and classification of objects. The best results of kappa in the comparison of algorithms of classification were obtained with SMO (0.8182) and Random Forest (0.8117). In the evaluation of datasets the kappa values of the photogrammetry orthomosaic and the combination of Sentinel 1 and 2 have similar values using the C4.5 algorithm.

scholarly journals Application of the empirical Bayes approach to nonparametric testing for high-dimensional data

2010 ◽  
Vol 51 ◽  
Author(s):  
Gintautas Jakimauskas ◽  
Jurgis Sušinskas
Keyword(s):  
Empirical Bayes ◽  
High Dimensional Data ◽  
High Dimensional ◽  
Sequential Data ◽  
Data Partition ◽  
Test Statistics ◽  
Computationally Efficient ◽  
Small Power ◽  
Nonparametric Testing ◽  
Empirical Bayes Estimators

In [5] a simple, data-driven and computationally efficient procedure of (nonparametric) testing for high-dimensional data have been introduced. The procedure is based on randomization and resampling, a special sequential data partition procedure, and χ2-type test statistics. However, the χ2 test has small power when deviations from the null hypothesis are small or sparse. In this note test statistics based on the nonparametric maximum likelihood and the empirical Bayes estimators.

scholarly journals EFFICIENCY ESTIMATION OF TRANSPORT COMPANIES' ACTIVITY

Transport ◽  
2003 ◽  
Vol 18 (2) ◽  
pp. 61-65 ◽  
Author(s):  
Andrius Vyskupaitis
Keyword(s):  
Classification Problem ◽  
Transport Systems ◽  
Problem Solution ◽  
Main Task ◽  
Second Stage ◽  
Efficiency Estimation ◽  
Economic Indexes ◽  
Selection Of

In this article methodological subjects of activities efficiency research of the transport companies as well as other complex systems are analyzed. Methodically it is the most important to select estimation indexes of efficiency of searching object activities. After the system of indexes is formed, it is determined that it is more useful to use the system of technical economic indexes in order to estimate the level of efficiency of the activities of transport companies. It is so, because none of the separate indexes individually is able comprehensively to reflect the activities of transport systems or separate companies. Using the proposed method it is possible to research the great amount of objects according to numerous indexes. The main task is to form conditionally monolithic groups from the totality of objects. The level of activities of the objects in these groups should be similar. It would be possible to solve this task with the help of the image identification theory. The essence of this theory is to used necessary algorithm for the identification of searching objects signs. On this basis each object is reckoned in a certain monolithic objects group. Next step is the use of classification algorithms, which enable to classify the whole of searching objects. In this article you would fmd two main stages of classification problem solution. In the first stage the expansion of the objects into monolithic groups according to one of the indexes goes. The quality of this stage depends on the amount of the groups and on the selection of a concrete index. In the second stage the final objects expansion into monolithic groups according to the whole of selected technicaleconomic level indexes goes. Here is the manifold classification of the objects. Its results enable to determine the efficiency level of transport systems activities as well as to improve the quality of planning transport company's activities.

Classification of Acceleration Waveforms during Walking by Wavelet Transform

1997 ◽  
Vol 36 (04/05) ◽  
pp. 356-359 ◽  
Author(s):  
M. Sekine ◽  
M. Ogawa ◽  
T. Togawa ◽  
Y. Fukui ◽  
T. Tamura
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Center Of Gravity ◽  
Dynamic Responses ◽  
Sequential Data ◽  
Acceleration Signal ◽  
Continuous Dynamic

Abstract:In this study we have attempted to classify the acceleration signal, while walking both at horizontal level, and upstairs and downstairs, using wavelet analysis. The acceleration signal close to the body’s center of gravity was measured while the subjects walked in a corridor and up and down a stairway. The data for four steps were analyzed and the Daubecies 3 wavelet transform was applied to the sequential data. The variables to be discriminated were the waveforms related to levels -4 and -5. The sum of the square values at each step was compared at levels -4 and -5. Downstairs walking could be discriminated from other types of walking, showing the largest value for level -5. Walking at horizontal level was compared with upstairs walking for level -4. It was possible to discriminate the continuous dynamic responses to walking by the wavelet transform.

Use of photodynamic therapy for photodamage skin (review of literature)

2019 ◽  
Vol 1 (7) ◽  
pp. 19-23
Author(s):  
S. I. Surkichin ◽  
N. V. Gryazeva ◽  
L. S. Kholupova ◽  
N. V. Bochkova
Keyword(s):  
Photodynamic Therapy ◽  
Comparative Evaluation ◽  
Clinical Manifestations ◽  
Light Sources ◽  
Review Of Literature ◽  
Photosensitizing Agents ◽  
Selection Of

The article provides an overview of the use of photodynamic therapy for photodamage of the skin. The causes, pathogenesis and clinical manifestations of skin photodamage are considered. The definition, principle of action of photodynamic therapy, including the sources of light used, the classification of photosensitizers and their main characteristics are given. Analyzed studies that show the effectiveness and comparative evaluation in the selection of various light sources and photosensitizing agents for photodynamic therapy in patients with clinical manifestations of photodamage.

Philosophcal review of h. white̕s tropological theory in the context of the new philosophy of history

2020 ◽  
Vol 3 (152) ◽  
pp. 92-99
Author(s):  
S. M. Geiko ◽  
◽  
O. D. Lauta
Keyword(s):  
Modern Science ◽  
Historical Knowledge ◽  
Text Organization ◽  
The Social ◽  
History Of ◽  
Actual Material ◽  
The Common ◽  
Historical Nature ◽  
Selection Of

The article provides a philosophical analysis of the tropological theory of the history of H. White. The researcher claims that history is a specific kind of literature, and the historical works is the connection of a certain set of research and narrative operations. The first type of operation answers the question of why the event happened this way and not the other. The second operation is the social description, the narrative of events, the intellectual act of organizing the actual material. According to H. White, this is where the set of ideas and preferences of the researcher begin to work, mainly of a literary and historical nature. Explanations are the main mechanism that becomes the common thread of the narrative. The are implemented through using plot (romantic, satire, comic and tragic) and trope systems – the main stylistic forms of text organization (metaphor, metonymy, synecdoche, irony). The latter decisively influenced for result of the work historians. Historiographical style follows the tropological model, the selection of which is determined by the historian’s individual language practice. When the choice is made, the imagination is ready to create a narrative. Therefore, the historical understanding, according to H. White, can only be tropological. H. White proposes a new methodology for historical research. During the discourse, adequate speech is created to analyze historical phenomena, which the philosopher defines as prefigurative tropological movement. This is how history is revealed through the art of anthropology. Thus, H. White’s tropical history theory offers modern science f meaningful and metatheoretically significant. The structure of concepts on which the classification of historiographical styles can be based and the predictive function of philosophy regarding historical knowledge can be refined.

Using clusterization principles for the selection of repair sections of main oil pipelines based on diagnostic data

2011 ◽  
Vol 8 (1) ◽  
pp. 201-210
Author(s):  
R.M. Bogdanov
Keyword(s):  
Cluster Analysis ◽  
Defect Density ◽  
Density Variation ◽  
Distance Functions ◽  
Oil Pipeline ◽  
Oil Pipelines ◽  
Classification Of Images ◽  
Main Oil Pipeline ◽  
Selection Of

The problem of determining the repair sections of the main oil pipeline is solved, basing on the classification of images using distance functions and the clustering principle, The criteria characterizing the cluster are determined by certain given values, based on a comparison with which the defect is assigned to a given cluster, procedures for the redistribution of defects in cluster zones are provided, and the cluster zones parameters are being changed. Calculations are demonstrating the range of defect density variation depending on pipeline sections and the universal capabilities of linear objects configuration with arbitrary density, provided by cluster analysis.

Negative Staining: a Valuable Technique for Studying Subcellular Components

1997 ◽  
Vol 3 (S2) ◽  
pp. 341-342
Author(s):  
Sara E. Miller
Keyword(s):  
Negative Staining ◽  
Cell Organelles ◽  
Preparation Time ◽  
Nucleic Acid Probes ◽  
Virus Identification ◽  
High Particle ◽  
Thin Sectioning ◽  
Particle Counts ◽  
Selection Of

Negative staining is the most frequently used procedure for preparing particulate specimens, e.g., cell organelles, macromolecules, and viruses, for electron microscopy (Figs. 1-4). The main advantage is that it is rapid, requiring only minutes of preparation time. Another is that it avoids some of the harsh chemicals, e.g., organic solvents, used in thin sectioning. Also, it does not require advanced technical skill. It is widely used in virology, both in classification of viruses as well as diagnosis of viral diseases. Notwithstanding the necessity for fairly high particle counts, virus identification by negative staining is advantageous in not requiring specific reagents such as antibodies, nucleic acid probes, or protein standards which necessitate prior knowledge of potential pathogens for selection of the proper reagent. Furthermore, it does not require viable virions as does growth in tissue culture. Another procedure that uses negative contrasting is ultrathin cryosectioning (Fig. 5).In 1954 Farrant was the first to publish negatively stained material, ferritin particles.

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