Class information for: |
Basic class information |
Class id | #P | Avg. number of references |
Database coverage of references |
---|---|---|---|
26534 | 252 | 22.5 | 39% |
Hierarchy of classes |
The table includes all classes above and classes immediately below the current class. |
Cluster id | Level | Cluster label | #P |
---|---|---|---|
9 | 4 | COMPUTER SCIENCE, THEORY & METHODS//COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE//COMPUTER SCIENCE, INFORMATION SYSTEMS | 1247339 |
211 | 3 | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE//IEEE TRANSACTIONS ON NEURAL NETWORKS//DATA MINING | 51632 |
2769 | 2 | SELF ORGANIZING MAP//PRINCIPAL CURVES//PRINCIPAL POINTS | 3152 |
26534 | 1 | PROJECTION PURSUIT//SPHERING//POSTERIOR CLASS PROBABILITIES | 252 |
Terms with highest relevance score |
rank | Term | termType | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|---|
1 | PROJECTION PURSUIT | authKW | 512039 | 12% | 15% | 29 |
2 | SPHERING | authKW | 363516 | 1% | 100% | 3 |
3 | POSTERIOR CLASS PROBABILITIES | authKW | 272635 | 1% | 75% | 3 |
4 | ASYMMETRIC CLASSIFICATION PROBLEMS | authKW | 242344 | 1% | 100% | 2 |
5 | CONVEX AND PIECEWISE LINEAR CPL CRITERION FUNCTIONS | authKW | 242344 | 1% | 100% | 2 |
6 | FISHERS CLASSIFIER | authKW | 242344 | 1% | 100% | 2 |
7 | LEARNING OBJECTIVE FUNCTIONS | authKW | 242344 | 1% | 100% | 2 |
8 | LINEAR SEPARABILITY OF DATA SETS | authKW | 242344 | 1% | 100% | 2 |
9 | MINIMUM MISCLASSIFICATION ERROR | authKW | 242344 | 1% | 100% | 2 |
10 | NORMALLY DISTRIBUTED CLASSES | authKW | 242344 | 1% | 100% | 2 |
Web of Science journal categories |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | Computer Science, Artificial Intelligence | 5824 | 40% | 0% | 100 |
2 | Statistics & Probability | 2203 | 23% | 0% | 58 |
3 | Computer Science, Theory & Methods | 562 | 13% | 0% | 34 |
4 | Engineering, Electrical & Electronic | 448 | 26% | 0% | 66 |
5 | Computer Science, Interdisciplinary Applications | 169 | 8% | 0% | 19 |
6 | Computer Science, Information Systems | 109 | 6% | 0% | 15 |
7 | Computer Science, Cybernetics | 104 | 2% | 0% | 5 |
8 | Mathematics, Interdisciplinary Applications | 47 | 4% | 0% | 9 |
9 | Automation & Control Systems | 46 | 3% | 0% | 8 |
10 | Mathematical & Computational Biology | 46 | 3% | 0% | 7 |
Address terms |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | DEPARTAMENTAL I | 121172 | 0% | 100% | 1 |
2 | DIPARTIMENTO AUTOMAZ ELETTROMAGNETISMO INGN INFOM | 121172 | 0% | 100% | 1 |
3 | ESTAD ECONOMETRICA | 121172 | 0% | 100% | 1 |
4 | IST NAZL GEOFIS VULCANOL BOLOGNA | 121172 | 0% | 100% | 1 |
5 | KNOWLEDGE SOC MANAGEMENT | 121172 | 0% | 100% | 1 |
6 | LOWELL SLOAN MANAGEMENT | 121172 | 0% | 100% | 1 |
7 | TECNOL COMINICAC | 121172 | 0% | 100% | 1 |
8 | TEOR DENAL COMUN INGN TELEMAT | 121172 | 0% | 100% | 1 |
9 | TEOR SENAL COMUNICAC ING TELEMAT | 121172 | 0% | 100% | 1 |
10 | TOULOUSE ECON GREMAQ IMT | 121172 | 0% | 100% | 1 |
Journals |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | IEEE TRANSACTIONS ON NEURAL NETWORKS | 9430 | 6% | 1% | 15 |
2 | PATTERN RECOGNITION | 6378 | 8% | 0% | 19 |
3 | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 2124 | 4% | 0% | 9 |
4 | STATISTICS AND COMPUTING | 1910 | 2% | 0% | 4 |
5 | MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING | 1646 | 1% | 0% | 3 |
6 | COMPUTATIONAL STATISTICS & DATA ANALYSIS | 1557 | 3% | 0% | 8 |
7 | CONTRIBUTIONS TO STATISTICS | 1371 | 1% | 0% | 3 |
8 | JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS | 1111 | 1% | 0% | 3 |
9 | ANNALS OF STATISTICS | 1101 | 2% | 0% | 6 |
10 | IET COMPUTER VISION | 1083 | 1% | 0% | 2 |
Author Key Words |
Core articles |
The table includes core articles in the class. The following variables is taken into account for the relevance score of an article in a cluster c: (1) Number of references referring to publications in the class. (2) Share of total number of active references referring to publications in the class. (3) Age of the article. New articles get higher score than old articles. (4) Citation rate, normalized to year. |
Rank | Reference | # ref. in cl. |
Shr. of ref. in cl. |
Citations |
---|---|---|---|---|
1 | ESPEZUA, S , VILLANUEVA, E , MACIEL, CD , (2014) TOWARDS AN EFFICIENT GENETIC ALGORITHM OPTIMIZER FOR SEQUENTIAL PROJECTION PURSUIT.NEUROCOMPUTING. VOL. 123. ISSUE . P. 40-48 | 13 | 62% | 6 |
2 | RUEDA, L , HERRERA, M , (2006) A THEORETICAL COMPARISON OF TWO LINEAR DIMENSIONALITY REDUCTION TECHNIQUES.PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS AND APPLICATIONS, PROCEEDINGS. VOL. 4225. ISSUE . P. 624 -633 | 11 | 92% | 0 |
3 | RUEDA, L , (2004) SELECTING THE BEST HYPERPLANE IN THE FRAMEWORK OF OPTIMAL PAIRWISE LINEAR CLASSIFIERS.PATTERN RECOGNITION LETTERS. VOL. 25. ISSUE 1. P. 49-62 | 10 | 100% | 8 |
4 | ALI, ML , RUEDA, L , HERRERA, M , (2006) ON THE PERFORMANCE OF CHERNOFF-DISTANCE-BASED LINEAR DIMENSIONALITY REDUCTION TECHNIQUES.ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS. VOL. 4013. ISSUE . P. 467 -478 | 10 | 91% | 3 |
5 | RUEDA, L , (2004) AN EFFICIENT APPROACH TO COMPUTE THE THRESHOLD FOR MULTI-DIMENSIONAL LINEAR CLASSIFIERS.PATTERN RECOGNITION. VOL. 37. ISSUE 4. P. 811-826 | 10 | 91% | 3 |
6 | RUEDA, L , (2003) A NEW APPROACH THAT SELECTS A SINGLE HYPERPLANE FROM THE OPTIMAL PAIRWISE LINEAR CLASSIFIER.PROGRESS IN PATTERN RECOGNITION, SPEECH AND IMAGE ANALYSIS. VOL. 2905. ISSUE . P. 521-528 | 9 | 100% | 0 |
7 | RUEDA, L , HERRERA, M , (2006) A NEW APPROACH TO MULTI-CLASS LINEAR DIMENSIONALITY REDUCTION.PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS AND APPLICATIONS, PROCEEDINGS. VOL. 4225. ISSUE . P. 634 -643 | 9 | 75% | 5 |
8 | RUEDA, L , HERRERA, M , (2006) A NEW LINEAR DIMENSIONALITY REDUCTION TECHNIQUE BASED ON CHERNOFF DISTANCE.ADVANCES IN ARTIFICIAL INTELLIGENCE - IBERAMIA-SBIA 2006, PROCEEDINGS. VOL. 4140. ISSUE . P. 299 -308 | 8 | 80% | 0 |
9 | ROHATSCH, T , POPPEL, G , WERNER, H , (2006) PROJECTION PURSUIT FOR ANALYZING DATA FROM SEMICONDUCTOR ENVIRONMENTS.IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING. VOL. 19. ISSUE 1. P. 87-94 | 7 | 88% | 1 |
10 | BERRO, A , MARIE-SAINTE, SL , RUIZ-GAZEN, A , (2010) GENETIC ALGORITHMS AND PARTICLE SWARM OPTIMIZATION FOR EXPLORATORY PROJECTION PURSUIT.ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE. VOL. 60. ISSUE 1-2. P. 153 -178 | 8 | 67% | 3 |
Classes with closest relation at Level 1 |