Nikhil Pal | Indian Statistical Institute, Calcutta (original) (raw)

Papers by Nikhil Pal

Research paper thumbnail of Executive Advisory Board

ieeexplore.ieee.org

... ANCA RALESCU ECE & CS Dept. Univ. of Cincinnati ML 0030 Cincinnat... more ... ANCA RALESCU ECE & CS Dept. Univ. of Cincinnati ML 0030 Cincinnati, OH 45221 LLOREN VALVERDE Dept. ... RICHARD TONG Advanced Decision Sys. ENRIC TRILLAS Universidad Politch./Madrid RONALD YAGER Iona College TAKESHI YAMAKAWA Kyushu Inst. ...

Research paper thumbnail of Robust Consensus: A New Measure for Multicriteria Robust Group Decision Making Problems Using Evolutionary Approach

Lecture Notes in Computer Science, 2014

Research paper thumbnail of Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering

BMC bioinformatics, 2007

The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, ... more The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell tumor (SRBCT) and thus often leads to misdiagnosis. Identification of biomarkers for distinguishing these cancers is a well studied problem. Existing methods typically evaluate each gene separately and do not take into account the nonlinear interaction between genes and the tools that are used to design the diagnostic prediction system. Consequently, more genes are usually identified as necessary for prediction. We propose a general scheme for finding a small set of biomarkers to design a diagnostic system for accurate classification of the cancer subgroups. We use multilayer networks with online gene selection ability and relational fuzzy clustering to identify a small set of biomarkers for accurate classification of the training and blind test cases of a well studied data set. Our method discerned just seven biomark...

Research paper thumbnail of A Multiobjective Genetic Programming-Based Ensemble for Simultaneous Feature Selection and Classification

IEEE transactions on cybernetics, Jan 6, 2015

We present an integrated algorithm for simultaneous feature selection (FS) and designing of diver... more We present an integrated algorithm for simultaneous feature selection (FS) and designing of diverse classifiers using a steady state multiobjective genetic programming (GP), which minimizes three objectives: 1) false positives (FPs); 2) false negatives (FNs); and 3) the number of leaf nodes in the tree. Our method divides a c-class problem into c binary classification problems. It evolves c sets of genetic programs to create c ensembles. During mutation operation, our method exploits the fitness as well as unfitness of features, which dynamically change with generations with a view to using a set of highly relevant features with low redundancy. The classifiers of iii{th} class determine the {net belongingness} of an unknown data point to the iii{th} class using a weighted voting scheme, which makes use of the FP and FN mistakes made on the training data. We test our method on eight microarray and 11 text data sets with diverse number of classes (from 2 to 44), large number of featur...

Research paper thumbnail of A Review on Image Segmentation Techniques

Pattern recognition, Jan 1, 1993

Many image segmentation techniques are available in the literature. Some of these techniques use ... more Many image segmentation techniques are available in the literature. Some of these techniques use only the gray level histogram, some use spatial details while others use fuzzy set theoretic approaches. Most of these techniques are not suitable for noisy environments. Some ...

Research paper thumbnail of On cluster validity for the fuzzy c-means model

Fuzzy Systems, IEEE Transactions on, Jan 1, 1995

Research paper thumbnail of Some new indexes of cluster validity

Systems, Man, and Cybernetics, Part B: …, Jan 1, 1998

Research paper thumbnail of Generalized clustering networks and Kohonen's self-organizing scheme

Neural Networks, IEEE …, Jan 1, 1993

Research paper thumbnail of Fuzzy Kohonen clustering networks

Pattern recognition, Jan 1, 1994

Research paper thumbnail of A robust self-tuning scheme for PI-and PD-type fuzzy controllers

Fuzzy Systems, IEEE Transactions on, Jan 1, 1999

... results for some typical second-order linear as well as nonlinear processes using both of ...... more ... results for some typical second-order linear as well as nonlinear processes using both of ... MUDI AND PAL: ROBUST SELF-TUNING SCHEME FOR PI-AND PD-TYPE FUZZY CONTROLLERS 9 (a) ... Since peak overshoot and rise time usually conflict each other they may not be ...

Research paper thumbnail of A possibilistic fuzzy c-means clustering algorithm

Fuzzy Systems, IEEE …, Jan 1, 2005

Research paper thumbnail of Entropic thresholding

Signal processing, Jan 1, 1989

... 5(a) and 5(b) represent the input image of Abraham Lincoln and its gray level histogram, resp... more ... 5(a) and 5(b) represent the input image of Abraham Lincoln and its gray level histogram, respectively. ... [3] JN Kapur, PK Sahoo and AKC Wong, "A new method for grey-level picturethresholding using the entropy of the histogram", Comp. Graphics, Vision and Image Proc. ...

Research paper thumbnail of Entropy: a new definition and its applications

… , Man and Cybernetics, IEEE Transactions on, Jan 1, 1991

Research paper thumbnail of A mixed c-means clustering model

Fuzzy Systems, 1997., …, Jan 1, 1997

A Mixed c-Means Clustering Model Nikhil R. Pal and Kuhu Pal Machine Intelligence Unlit Indian Sta... more A Mixed c-Means Clustering Model Nikhil R. Pal and Kuhu Pal Machine Intelligence Unlit Indian Statistical Institute 203 B. T. Road Calcutta - 700 035 , India ... where U E Mfcn, V = (vl, v2, ..., vc) is a vector of (unknown) cluster centers (weights or prototypes), vi E sP for 1 I i I c and ...

Research paper thumbnail of Executive Advisory Board

ieeexplore.ieee.org

... ANCA RALESCU ECE & CS Dept. Univ. of Cincinnati ML 0030 Cincinnat... more ... ANCA RALESCU ECE & CS Dept. Univ. of Cincinnati ML 0030 Cincinnati, OH 45221 LLOREN VALVERDE Dept. ... RICHARD TONG Advanced Decision Sys. ENRIC TRILLAS Universidad Politch./Madrid RONALD YAGER Iona College TAKESHI YAMAKAWA Kyushu Inst. ...

Research paper thumbnail of Robust Consensus: A New Measure for Multicriteria Robust Group Decision Making Problems Using Evolutionary Approach

Lecture Notes in Computer Science, 2014

Research paper thumbnail of Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering

BMC bioinformatics, 2007

The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, ... more The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell tumor (SRBCT) and thus often leads to misdiagnosis. Identification of biomarkers for distinguishing these cancers is a well studied problem. Existing methods typically evaluate each gene separately and do not take into account the nonlinear interaction between genes and the tools that are used to design the diagnostic prediction system. Consequently, more genes are usually identified as necessary for prediction. We propose a general scheme for finding a small set of biomarkers to design a diagnostic system for accurate classification of the cancer subgroups. We use multilayer networks with online gene selection ability and relational fuzzy clustering to identify a small set of biomarkers for accurate classification of the training and blind test cases of a well studied data set. Our method discerned just seven biomark...

Research paper thumbnail of A Multiobjective Genetic Programming-Based Ensemble for Simultaneous Feature Selection and Classification

IEEE transactions on cybernetics, Jan 6, 2015

We present an integrated algorithm for simultaneous feature selection (FS) and designing of diver... more We present an integrated algorithm for simultaneous feature selection (FS) and designing of diverse classifiers using a steady state multiobjective genetic programming (GP), which minimizes three objectives: 1) false positives (FPs); 2) false negatives (FNs); and 3) the number of leaf nodes in the tree. Our method divides a c-class problem into c binary classification problems. It evolves c sets of genetic programs to create c ensembles. During mutation operation, our method exploits the fitness as well as unfitness of features, which dynamically change with generations with a view to using a set of highly relevant features with low redundancy. The classifiers of iii{th} class determine the {net belongingness} of an unknown data point to the iii{th} class using a weighted voting scheme, which makes use of the FP and FN mistakes made on the training data. We test our method on eight microarray and 11 text data sets with diverse number of classes (from 2 to 44), large number of featur...

Research paper thumbnail of A Review on Image Segmentation Techniques

Pattern recognition, Jan 1, 1993

Many image segmentation techniques are available in the literature. Some of these techniques use ... more Many image segmentation techniques are available in the literature. Some of these techniques use only the gray level histogram, some use spatial details while others use fuzzy set theoretic approaches. Most of these techniques are not suitable for noisy environments. Some ...

Research paper thumbnail of On cluster validity for the fuzzy c-means model

Fuzzy Systems, IEEE Transactions on, Jan 1, 1995

Research paper thumbnail of Some new indexes of cluster validity

Systems, Man, and Cybernetics, Part B: …, Jan 1, 1998

Research paper thumbnail of Generalized clustering networks and Kohonen's self-organizing scheme

Neural Networks, IEEE …, Jan 1, 1993

Research paper thumbnail of Fuzzy Kohonen clustering networks

Pattern recognition, Jan 1, 1994

Research paper thumbnail of A robust self-tuning scheme for PI-and PD-type fuzzy controllers

Fuzzy Systems, IEEE Transactions on, Jan 1, 1999

... results for some typical second-order linear as well as nonlinear processes using both of ...... more ... results for some typical second-order linear as well as nonlinear processes using both of ... MUDI AND PAL: ROBUST SELF-TUNING SCHEME FOR PI-AND PD-TYPE FUZZY CONTROLLERS 9 (a) ... Since peak overshoot and rise time usually conflict each other they may not be ...

Research paper thumbnail of A possibilistic fuzzy c-means clustering algorithm

Fuzzy Systems, IEEE …, Jan 1, 2005

Research paper thumbnail of Entropic thresholding

Signal processing, Jan 1, 1989

... 5(a) and 5(b) represent the input image of Abraham Lincoln and its gray level histogram, resp... more ... 5(a) and 5(b) represent the input image of Abraham Lincoln and its gray level histogram, respectively. ... [3] JN Kapur, PK Sahoo and AKC Wong, "A new method for grey-level picturethresholding using the entropy of the histogram", Comp. Graphics, Vision and Image Proc. ...

Research paper thumbnail of Entropy: a new definition and its applications

… , Man and Cybernetics, IEEE Transactions on, Jan 1, 1991

Research paper thumbnail of A mixed c-means clustering model

Fuzzy Systems, 1997., …, Jan 1, 1997

A Mixed c-Means Clustering Model Nikhil R. Pal and Kuhu Pal Machine Intelligence Unlit Indian Sta... more A Mixed c-Means Clustering Model Nikhil R. Pal and Kuhu Pal Machine Intelligence Unlit Indian Statistical Institute 203 B. T. Road Calcutta - 700 035 , India ... where U E Mfcn, V = (vl, v2, ..., vc) is a vector of (unknown) cluster centers (weights or prototypes), vi E sP for 1 I i I c and ...