- Microsoft Research
... • At some point we need indices to limit search parallel data search and analysis • This is where databases can help • Next generation technique: Data Exploration – Bring the analysis to the data! ...
... • At some point we need indices to limit search parallel data search and analysis • This is where databases can help • Next generation technique: Data Exploration – Bring the analysis to the data! ...
MIS 451/551, Spring 2000
... E1 = -( 4/4 * log2(4/4) + 0/4 * log2(0/4)) = -( 1* log21 + 0 * log20) E2 = -( 3/6 * log2(3/6) + 3/6 * log2(3/6)) = -( 0.5 * log20.5 + 0.5 * log20.5) d) ...
... E1 = -( 4/4 * log2(4/4) + 0/4 * log2(0/4)) = -( 1* log21 + 0 * log20) E2 = -( 3/6 * log2(3/6) + 3/6 * log2(3/6)) = -( 0.5 * log20.5 + 0.5 * log20.5) d) ...
A Data Mining Approach for Retailing Bank
... Field Test Results Top 5% of 750000 customer = 37500 (output from the data mining prediction list), create 2 groups with 10000 customers each by random sampling from 37500 top customers from the prediction list sorted by the score Group 1: the marketing department contacted each customer and offere ...
... Field Test Results Top 5% of 750000 customer = 37500 (output from the data mining prediction list), create 2 groups with 10000 customers each by random sampling from 37500 top customers from the prediction list sorted by the score Group 1: the marketing department contacted each customer and offere ...
Data Mining - KSU Web Home
... DSS: Information technology to help the knowledge worker (executive, manager, analyst) make faster and better decisions what were the sales volumes by region and product category for the last year? How did the share price of computer manufacturers correlate with quarterly profits over the past ...
... DSS: Information technology to help the knowledge worker (executive, manager, analyst) make faster and better decisions what were the sales volumes by region and product category for the last year? How did the share price of computer manufacturers correlate with quarterly profits over the past ...
1 Introduction
... Materials are an integral part of civilization. Today the systematic and intense study of their properties and the exploitation of novel preparation and processing methods have revolutionized almost every aspect of our lives [1-3]. Optoelectronics, for example, which enable fast and reliable communi ...
... Materials are an integral part of civilization. Today the systematic and intense study of their properties and the exploitation of novel preparation and processing methods have revolutionized almost every aspect of our lives [1-3]. Optoelectronics, for example, which enable fast and reliable communi ...
PowerPoint
... Diagnosis: Linux machines with > 3GB have a different memory layout that breaks some programs that do inappropriate pointer arithmetic. ...
... Diagnosis: Linux machines with > 3GB have a different memory layout that breaks some programs that do inappropriate pointer arithmetic. ...
Classification of Parkinson`s Disease Using Data Mining Techniques
... Copyright: © 2015 Khan SU. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ...
... Copyright: © 2015 Khan SU. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ...
An Introduction to Data Mining
... • Approximates function by piece wise constant regions • Does not require any prior knowledge of data distribution, works well on noisy data. • Has been applied to: – classify medical patients based on the disease, – equipment malfunction by cause, – loan applicant by likelihood of payment. ...
... • Approximates function by piece wise constant regions • Does not require any prior knowledge of data distribution, works well on noisy data. • Has been applied to: – classify medical patients based on the disease, – equipment malfunction by cause, – loan applicant by likelihood of payment. ...
data mining: pharmacovigilance signals of benzodiazepines and
... Information Component, and EBGM: Empiric Bayesian Geometric Mean) on spontaneous reports of SSTD-ADR due to benzodiazepines commercialized in USA, registered into FAERS. All statistical algorithms were calculated from 2x2 contingency tables, according to literature: PRR – 1.96SE (standar error) (wit ...
... Information Component, and EBGM: Empiric Bayesian Geometric Mean) on spontaneous reports of SSTD-ADR due to benzodiazepines commercialized in USA, registered into FAERS. All statistical algorithms were calculated from 2x2 contingency tables, according to literature: PRR – 1.96SE (standar error) (wit ...
Vadis Smart Toolbox For Big Data Analytics
... and R&D teams for ready-to-use or customizable solutions and processes. »» Do you have problems in uniquely identifying your own customers from your databases or public databases? Try out our deduplication processes and you’ll be amazed by its efficiency and accuracy. »» Do you have general Data Q ...
... and R&D teams for ready-to-use or customizable solutions and processes. »» Do you have problems in uniquely identifying your own customers from your databases or public databases? Try out our deduplication processes and you’ll be amazed by its efficiency and accuracy. »» Do you have general Data Q ...
DBMS File system
... Top-down design process; we designate subgroupings within an entity set that are distinctive from other entities in the set. ...
... Top-down design process; we designate subgroupings within an entity set that are distinctive from other entities in the set. ...
Similarity Analysis in Social Networks Based on Collaborative Filtering
... This is the simplest scenario. Let x be the point to be labeled. Find the point closest to x. Let it be y. Now nearest neighbor rule asks to assign the label of y to x. This seems too simplistic and sometimes even counter intuitive. If you feel that this procedure will result a huge error, you are r ...
... This is the simplest scenario. Let x be the point to be labeled. Find the point closest to x. Let it be y. Now nearest neighbor rule asks to assign the label of y to x. This seems too simplistic and sometimes even counter intuitive. If you feel that this procedure will result a huge error, you are r ...
Class4.1 - Other Methods and Success Stories
... Lots of data is being automatically collected and warehoused Web ...
... Lots of data is being automatically collected and warehoused Web ...
Lecture X
... Kernel-based framework is very powerful, flexible SVMs work very well in practice, even with very small training sample sizes ...
... Kernel-based framework is very powerful, flexible SVMs work very well in practice, even with very small training sample sizes ...
Theme-based Opinion Analysis Incorporating Social Relationships
... Using well established data mining techniques, it can explore the potential of this valuable data in order to better manage their projects and do produce higher-quality software systems that are delivered on time and with in budget. ...
... Using well established data mining techniques, it can explore the potential of this valuable data in order to better manage their projects and do produce higher-quality software systems that are delivered on time and with in budget. ...
lec1-feb3-10 - Ravikumar
... Computerization of businesses produce huge amount of data How to make best use of data? Knowledge discovered from data can be used for competitive advantage. Online businesses generate even larger data sets Online retailers (e.g., amazon.com) are largely driven by data mining. Web search ...
... Computerization of businesses produce huge amount of data How to make best use of data? Knowledge discovered from data can be used for competitive advantage. Online businesses generate even larger data sets Online retailers (e.g., amazon.com) are largely driven by data mining. Web search ...
A Data Mining Tutorial
... – Error rate on training set (resubstitution error) not useful because pruning will always increase error – Two common techniques are cost-complexity pruning and reduced-error pruning ...
... – Error rate on training set (resubstitution error) not useful because pruning will always increase error – Two common techniques are cost-complexity pruning and reduced-error pruning ...
Big-Data Tutorial
... • Latent Dirichlet Allocation • Singular value decomposition • Parallel Frequent Pattern mining • Complementary Naive Bayes classifier • Random forest decision tree based classifier ...
... • Latent Dirichlet Allocation • Singular value decomposition • Parallel Frequent Pattern mining • Complementary Naive Bayes classifier • Random forest decision tree based classifier ...
Free Doses of Data Science - Biomedical Computation Review
... a deal with the publisher: The book became free online just six months after publication. It’s an extra draw for students—not only is the course free, but the text is as well. The same is true for the Mining Massive Datasets MOOC. The statistical learning MOOC, offered on Stanford’s OpenEdX platform ...
... a deal with the publisher: The book became free online just six months after publication. It’s an extra draw for students—not only is the course free, but the text is as well. The same is true for the Mining Massive Datasets MOOC. The statistical learning MOOC, offered on Stanford’s OpenEdX platform ...
Nonlinear dimensionality reduction
High-dimensional data, meaning data that requires more than two or three dimensions to represent, can be difficult to interpret. One approach to simplification is to assume that the data of interest lie on an embedded non-linear manifold within the higher-dimensional space. If the manifold is of low enough dimension, the data can be visualised in the low-dimensional space.Below is a summary of some of the important algorithms from the history of manifold learning and nonlinear dimensionality reduction (NLDR). Many of these non-linear dimensionality reduction methods are related to the linear methods listed below. Non-linear methods can be broadly classified into two groups: those that provide a mapping (either from the high-dimensional space to the low-dimensional embedding or vice versa), and those that just give a visualisation. In the context of machine learning, mapping methods may be viewed as a preliminary feature extraction step, after which pattern recognition algorithms are applied. Typically those that just give a visualisation are based on proximity data – that is, distance measurements.