http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=2&f=G&l=50&co1=AND&d=PTXT&s1=yuta.INNM.&s2=fujitsu.ASNM.&OS=IN/yuta+AND+AN/fujitsu&RS=IN/yuta+AND+AN/fujitsu United States Patent 7,725,413 Yuta May 25, 2010 Generating two-class classification model for predicting chemical toxicity Abstract A method includes: a) preparing as training data a sample set that contains a plurality of samples belonging to a first class and a plurality of samples belonging to a second class; b) generating, by performing discriminant analysis on the sample set, a first discriminant function having a high classification characteristic for the first class and a second discriminant function having a high classification characteristic for the second class; c) by classifying the sample set using the first and second discriminant functions, isolating any sample whose classification results by the first and second discriminant functions do not match; d) forming a new sample set by grouping together any sample thus isolated, and repeating b) and c) by using the new sample set; and e) causing d) to stop when the number of samples each of whose classification results do not match in c) has decreased to or below a predetermined value. Inventors: Yuta; Kohtarou (Kawasaki, JP) Assignee: Fujitsu Limited (Kawasaki, JP) Appl. No.: 12/453,247 Filed: May 4, 2009 --------------------------------------------------------------------------------------------------------------------------------------------------------------------- http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=6&f=G&l=50&co1=AND&d=PTXT&s1=yuta.INNM.&s2=fujitsu.ASNM.&OS=IN/yuta+AND+AN/fujitsu&RS=IN/yuta+AND+AN/fujitsu United States Patent 5,796,632 Yuta August 18, 1998 Method for converting information of peripheral space of a three-dimensional compound structure into numerical data and method for converting interactions between a three-dimensional compound structure and peripheral space into numerical data Abstract A method for converting information of a peripheral space of a three-dimensional compound structure into numerical data is disclosed. This method comprises the steps of designating a peripheral region that includes the entire three-dimensional structure of a compound on the periphery thereof, designating a plurality of small regions in the peripheral region, generating a plurality of points in the peripheral region, calculating the interaction between the three-dimensional structure of a compound and each of points at least included in the points as numerical data so as to allocate the numerical data to corresponding individual points, and determining at least one of numerical data that represents each of the small regions corresponding to the numerical data allocated to each of the individual points. After a representative value of each small region is obtained, the representative value is supplied to a portion that performs various analyzing techniques such as the linear multiple regression method without any statistical defects. Inventors: Yuta; Kohtaro (Kawasaki, JP) Assignee: Fujitsu Limited (Kawasaki, JP) Appl. No.: 08/546,138 Filed: October 20, 1995 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- http://appft1.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1&f=G&l=50&co1=AND&d=PG01&s1=yuta.IN.&s2=fujitsu.AS.&OS=IN/yuta+AND+AN/fujitsu&RS=IN/yuta+AND+AN/fujitsu United States Patent Application 20110208495 Kind Code A1 YUTA; Kohtarou August 25, 2011 METHOD, SYSTEM, AND PROGRAM FOR GENERATING PREDICTION MODEL BASED ON MULTIPLE REGRESSION ANALYSIS Abstract A prediction model having high prediction accuracy for the prediction of a dependent variable is generated based on multiple regression analysis. The method includes: a) constructing an initial sample set from samples for each of which the measured value of the dependent variable is known; b) generating a multiple regression equation by performing multiple regression analysis on the sample set; c) calculating a residual value for each sample based on the multiple regression equation; d) identifying, based on the residual value, a sample that fits the multiple regression equation; e) constructing a new sample set by removing the identified sample from the initial sample set; and f) replacing the initial sample set by the new sample set, and repeating from a) to e), thereby generating a plurality of multiple regression equations and identifying a sample to which the multiple regression equation is applied. Inventors: YUTA; Kohtarou; (Kawasaki, JP) Assignee: Fujitsu Limited Kawasaki JP Serial No.: 019641 Series Code: 13 Filed: February 2, 2011 Current U.S. Class: 703/2 Class at Publication: 703/2 International Class: G06F 17/10 20060101 G06F017/10 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- http://appft1.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=2&f=G&l=50&co1=AND&d=PG01&s1=yuta.IN.&s2=fujitsu.AS.&OS=IN/yuta+AND+AN/fujitsu&RS=(IN/yuta+AND+AN/fujitsu) United States Patent Application 20110137841 Kind Code A1 YUTA; Kohtarou June 9, 2011 SAMPLE CLASS PREDICTION METHOD, PREDICTION PROGRAM, AND PREDICTION APPARATUS Abstract To predict the class of an unknown sample, a) a discriminant function for assigning each training sample to class 1 or class 2 is obtained, b) the discriminant score of each training sample and an unknown sample are calculated using the function, c) it is determined whether the score of the unknown sample is either not smaller than the largest score or not larger than the smallest score taken among all of the training samples, d) if the determination in c) is affirmative, the class of the unknown sample is determined based on the score of the unknown sample, e) if the determination in c) is negative, then the training samples having the largest score and the smallest score are removed to form a new training sample set from remaining training samples, and f) a) to e) are repeated. Inventors: YUTA; Kohtarou; (Narashino, JP) Assignee: FUJITSU LIMITED Kawasaki JP Serial No.: 019683 Series Code: 13 Filed: February 2, 2011 Current U.S. Class: 706/20 Class at Publication: 706/20 International Class: G06F 15/18 20060101 G06F015/18 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- http://appft1.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=3&f=G&l=50&co1=AND&d=PG01&s1=yuta.IN.&s2=fujitsu.AS.&OS=IN/yuta+AND+AN/fujitsu&RS=(IN/yuta+AND+AN/fujitsu) United States Patent Application 20100241598 Kind Code A1 YUTA; Kotaro September 23, 2010 METHOD, PROGRAM, AND APPARATUS FOR GENERATING TWO-CLASS CLASSIFICATION/PREDICTION MODEL Abstract A two-class classification/prediction model is generated in a simple operation by performing two-class classification with a classification rate substantially close to 100%. The two-class classification/prediction model is generated by a) obtaining a discriminant function for classifying a training sample set into two predetermined classes on the basis of an explanatory variable generated for each sample contained in the training sample set, b) calculating a discriminant score for each training sample by using the obtained discriminant function, c) determining, based on the calculated discriminant score, whether the training sample is correctly classified or not, d) determining a misclassified-sample region based on maximum and minimum discriminant scores taken from among misclassified samples in the training sample set, e) constructing a new training sample set by extracting the training samples contained in the misclassified-sample region, and f) repeating a) to e) for the new training sample set. Inventors: YUTA; Kotaro; (Narashino, JP) Correspondence Address: STAAS & HALSEY LLP SUITE 700, 1201 NEW YORK AVENUE, N.W. WASHINGTON DC 20005 US Assignee: FUJITSU LIMITED Kawasaki JP Serial No.: 795078 Series Code: 12 Filed: June 7, 2010 Current U.S. Class: 706/12 Class at Publication: 706/12 International Class: G06F 15/18 20060101 G06F015/18 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- http://appft1.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=4&f=G&l=50&co1=AND&d=PG01&s1=yuta.IN.&s2=fujitsu.AS.&OS=IN/yuta+AND+AN/fujitsu&RS=(IN/yuta+AND+AN/fujitsu) United States Patent Application 20100145896 Kind Code A1 YUTA; Koutarou June 10, 2010 COMPOUND PROPERTY PREDICTION APPARATUS, PROPERTY PREDICTION METHOD, AND PROGRAM FOR IMPLEMENTING THE METHOD Abstract A compound property prediction apparatus includes a training sample library (16) in which a parameter value and a value for a prediction item are preregistered for each individual one of a plurality of training samples; an input device (12) inputting data concerning an unknown sample; a parameter generating device (14) of the unknown sample; a similarity calculation device (18) which calculates the degree of similarity between the unknown sample and the individual one training sample; a sub-sample set construction device (20) which constructs a sub-sample set by extracting training samples whose degree of similarity to the unknown sample is not smaller than a predetermined threshold value; a prediction model construction device (22) which constructs a prediction model from the sub-sample set; and a prediction value calculation device (24) which calculates the prediction value of the unknown sample based on the prediction model. Inventors: YUTA; Koutarou; (Narashino, JP) Correspondence Address: STAAS & HALSEY LLP SUITE 700, 1201 NEW YORK AVENUE, N.W. WASHINGTON DC 20005 US Assignee: FUJITSU LIMITED Kawasaki JP Serial No.: 707878 Series Code: 12 Filed: February 18, 2010 Current U.S. Class: 706/12; 706/54 Class at Publication: 706/12; 706/54 International Class: G06F 15/18 20060101 G06F015/18 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- http://appft1.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=7&f=G&l=50&co1=AND&d=PG01&s1=yuta.IN.&s2=fujitsu.AS.&OS=IN/yuta+AND+AN/fujitsu&RS=(IN/yuta+AND+AN/fujitsu) United States Patent Application 20100070441 Kind Code A1 Yuta; Kohtarou March 18, 2010 Method, apparatus, and program for generating prediction model based on multiple regression analysis Abstract An objective variable prediction model based on multiple regression analysis and having high prediction accuracy is generated by a computer. The method includes the steps of: a) constructing an initial sample set from samples whose measured value of an objective variable is known; b) obtaining a calculated value of the objective variable using multiple regression analysis; c) extracting samples whose difference between the measured and the calculated value is not larger than a first value, and calculating a determination coefficient by applying multiple regression analysis to the extracted samples; d) repeating the step c) by changing the first value until the determination coefficient exceeds a second value; and e) performing two-class classification to classify the sub-sample set obtained at the end of the step d) as a first sub-sample set and remaining samples as a second sub-sample set, and calculating a discriminant function. Inventors: Yuta; Kohtarou; (Kawasaki, JP) Correspondence Address: STAAS & HALSEY LLP SUITE 700, 1201 NEW YORK AVENUE, N.W. WASHINGTON DC 20005 US Assignee: FUJITSU LIMITED Kawasaki JP Serial No.: 585512 Series Code: 12 Filed: September 16, 2009 Current U.S. Class: 706/12; 702/179; 706/54 Class at Publication: 706/12; 702/179; 706/54 International Class: G06F 15/18 20060101 G06F015/18 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- http://appft1.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=16&f=G&l=50&co1=AND&d=PG01&s1=Yuta.IN.&s2=Fujitsu.AS.&OS=IN/Yuta+AND+AN/Fujitsu&RS=IN/Yuta+AND+AN/Fujitsu United States Patent Application 20090222390 Kind Code A1 Yuta; Kohtarou September 3, 2009 Method, program and apparatus for generating two-class classification/prediction model Abstract A method includes: a) preparing as training data a sample set that contains a plurality of samples belonging to a first class and a plurality of samples belonging to a second class; b) generating, by performing discriminant analysis on the sample set, a first discriminant function having a high classification characteristic for the first class and a second discriminant function having a high classification characteristic for the second class; c) by classifying the sample set using the first and second discriminant functions, isolating any sample whose classification results by the first and second discriminant functions do not match; d) forming a new sample set by grouping together any sample thus isolated, and repeating b) and c) by using the new sample set; and e) causing d) to stop when the number of samples each of whose classification results do not match in c) has decreased to or below a predetermined value. Inventors: Yuta; Kohtarou; (Kawasaki, JP) Correspondence Address: STAAS & HALSEY LLP SUITE 700, 1201 NEW YORK AVENUE, N.W. WASHINGTON DC 20005 US Assignee: FUJITSU LIMITED Kawasaki JP Serial No.: 453247 Series Code: 12 Filed: May 4, 2009 Current U.S. Class: 706/13; 706/61 Class at Publication: 706/13; 706/61 International Class: G06N 3/00 20060101 G06N003/00; G06N 5/04 20060101 G06N005/04