Efficiently Exploring Multilevel Data with Recursive Partitioning.
... hypotheses are exhausted, it can be difficult to determine how best to explore the dataset to discover hidden relationships that could help to inform future research. Naturally, this practice is often done “by hand.” That is, the researcher in question will run multiple tests with different combinat ...
... hypotheses are exhausted, it can be difficult to determine how best to explore the dataset to discover hidden relationships that could help to inform future research. Naturally, this practice is often done “by hand.” That is, the researcher in question will run multiple tests with different combinat ...
Classification in spatial data mining
... – typically used in remote sensing image classification problems • see Appendix in 7.8 – In conditional probability we calculate the probability of A when we know that B has happened – In Bayes the question is: knowing that B happened what is the ...
... – typically used in remote sensing image classification problems • see Appendix in 7.8 – In conditional probability we calculate the probability of A when we know that B has happened – In Bayes the question is: knowing that B happened what is the ...
Association Rule Mining - Indian Statistical Institute
... Given data about some cars: engine size, number of seats, petrol / diesel, has airbag or not, price Problem 1: Given engine size of a new car, what is likely to be the price? Problem 2: Given the engine size of a new car, is it likely that the car is run by petrol? Problem 3: Given the engine ...
... Given data about some cars: engine size, number of seats, petrol / diesel, has airbag or not, price Problem 1: Given engine size of a new car, what is likely to be the price? Problem 2: Given the engine size of a new car, is it likely that the car is run by petrol? Problem 3: Given the engine ...
Springer Series in Statistics
... Tibshirani, and Jerome Friedman (Springer-Verlag, 2001). I saw in the book a heroic effort to integrate a very wide variety of data analysis tools. I learned from the book and was then able to approach more primary material within a useful framework. This book is my attempt to integrate some of the s ...
... Tibshirani, and Jerome Friedman (Springer-Verlag, 2001). I saw in the book a heroic effort to integrate a very wide variety of data analysis tools. I learned from the book and was then able to approach more primary material within a useful framework. This book is my attempt to integrate some of the s ...
Using SAS/Insight as an Introductory Data Mining Platform
... single-season batting statistics. The adjusted rsquared statistic (0.35) suggests an improvement over the single-season fielding model. Batting average, RB Is, and bases on balls all were statistically significant and had the correct sign, but runs and home runs were not significant. Multi-collinear ...
... single-season batting statistics. The adjusted rsquared statistic (0.35) suggests an improvement over the single-season fielding model. Batting average, RB Is, and bases on balls all were statistically significant and had the correct sign, but runs and home runs were not significant. Multi-collinear ...
Chapter 6 - Faculty & Research
... LOGISTIC REGRESSION • A statistical approach to classification of categorical outcome variables • Similar to multiple linear regression, but can be used when the outcome has more than two values • Uses data to produce a probability that a given case will fall into one of two classes (e.g., flights ...
... LOGISTIC REGRESSION • A statistical approach to classification of categorical outcome variables • Similar to multiple linear regression, but can be used when the outcome has more than two values • Uses data to produce a probability that a given case will fall into one of two classes (e.g., flights ...
microsoft stock quotes dependency analysis
... tightly related and supposing that they share the same trade market, there should also be a correlation between their stock values. Ideal result of this study would be an appropriate model, which would foretell chosen stock quote value on the basis of other company’s stock values with sufficient cer ...
... tightly related and supposing that they share the same trade market, there should also be a correlation between their stock values. Ideal result of this study would be an appropriate model, which would foretell chosen stock quote value on the basis of other company’s stock values with sufficient cer ...
Download Syllabus
... Since many of these discussions will be based on our analytic assignments (mini-cases), it is important that assigned work be done thoroughly and on time. Regular homeworks in this class are of the Type A variety, but with the group ...
... Since many of these discussions will be based on our analytic assignments (mini-cases), it is important that assigned work be done thoroughly and on time. Regular homeworks in this class are of the Type A variety, but with the group ...
L18: Lasso – Regularized Regression
... This models the residual as only in the y direction, and thus implicitly assumes that the X coordinates have no error. Thus when noise happens, it happens in the y-coordinate, and we want to minimize the effect of this. To do so, we can “regress to the mean” Consider a hard T RUE -FALSE test. Each s ...
... This models the residual as only in the y direction, and thus implicitly assumes that the X coordinates have no error. Thus when noise happens, it happens in the y-coordinate, and we want to minimize the effect of this. To do so, we can “regress to the mean” Consider a hard T RUE -FALSE test. Each s ...
Download Syllabus
... statistical theory, the scientific method and on some pragmatic epistemology. Second, is regression analysis mechanics and theory, including extensions of the basic linear regression model to logistic regressions, non-linear models and multivariate methods. Third, is forecasting of time series from ...
... statistical theory, the scientific method and on some pragmatic epistemology. Second, is regression analysis mechanics and theory, including extensions of the basic linear regression model to logistic regressions, non-linear models and multivariate methods. Third, is forecasting of time series from ...
Chapter12
... Alternating decision trees • Can also grow an option tree by incrementally adding nodes to it using a boosting algorithm • The resulting structure is called an alternating decision tree, with splitter nodes and prediction nodes • Prediction nodes are leaf nodes if no splitter nodes have been added ...
... Alternating decision trees • Can also grow an option tree by incrementally adding nodes to it using a boosting algorithm • The resulting structure is called an alternating decision tree, with splitter nodes and prediction nodes • Prediction nodes are leaf nodes if no splitter nodes have been added ...
Linear Regression Model for Edu
... analysis and presentation functions, including the statistical analysis and graphical representation of data. To determine the linear relationship between the variables it is recommended to run a Scatter plot before applying a regression analysis using PASW on the data set. If there is no linear rel ...
... analysis and presentation functions, including the statistical analysis and graphical representation of data. To determine the linear relationship between the variables it is recommended to run a Scatter plot before applying a regression analysis using PASW on the data set. If there is no linear rel ...
2006-01-20 princomp, ridge, PLS
... This can also be thought of as maximizing a Bayesian posterior, where the prior is [ ] ~ N (0,(2 )1 I p ) . This is also an example of data augmentation : Let X aug ...
... This can also be thought of as maximizing a Bayesian posterior, where the prior is [ ] ~ N (0,(2 )1 I p ) . This is also an example of data augmentation : Let X aug ...
Feature Extraction, Feature Selection and Machine Learning for
... correlated attributes, best first forward/backward search, reranking/tabu/greedy search, evolutionary/genetic algorithms, linear forward selection, particle swarm optimization); together with the dataset having all 48 attributes, we have 12 datasets with 15-48 predictive features. Twelve classificat ...
... correlated attributes, best first forward/backward search, reranking/tabu/greedy search, evolutionary/genetic algorithms, linear forward selection, particle swarm optimization); together with the dataset having all 48 attributes, we have 12 datasets with 15-48 predictive features. Twelve classificat ...
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing
... between the independent variables and the log of the odds of the dependent variable, transformations can be used to make the independent variables more linear. Examples of transformations include the square, cube, square root, cube root, and the log. Some complex methods have been developed to deter ...
... between the independent variables and the log of the odds of the dependent variable, transformations can be used to make the independent variables more linear. Examples of transformations include the square, cube, square root, cube root, and the log. Some complex methods have been developed to deter ...
DFA presentation
... but now used by statisticians also Based on how neurons function in brain ...
... but now used by statisticians also Based on how neurons function in brain ...
Data Mining: An Overview of Methods and Techniques
... how the risk index is lower for the most responsive customers. This is common in direct response and demonstrates ‘adverse selection’. In other words, the riskier prospects are often the most responsive. At some point in the process, a decision is made to mail a percent of the file. In this case, yo ...
... how the risk index is lower for the most responsive customers. This is common in direct response and demonstrates ‘adverse selection’. In other words, the riskier prospects are often the most responsive. At some point in the process, a decision is made to mail a percent of the file. In this case, yo ...
REMARKS FOR PREPARING TO THE EXAM (FIRST ATTEMPT
... This note should give you some useful hints on topics which are the basis for preparing the exam on the Data Mining and Data Analysis course for Software Engineering specialization at Computer Science. However, you should treat them as a kind of warnings what seems to be the most important in Magdal ...
... This note should give you some useful hints on topics which are the basis for preparing the exam on the Data Mining and Data Analysis course for Software Engineering specialization at Computer Science. However, you should treat them as a kind of warnings what seems to be the most important in Magdal ...
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing
... between the independent variables and the log of the odds of the dependent variable, transformations can be used to make the independent variables more linear. Examples of transformations include the square, cube, square root, cube root, and the log. Some complex methods have been developed to deter ...
... between the independent variables and the log of the odds of the dependent variable, transformations can be used to make the independent variables more linear. Examples of transformations include the square, cube, square root, cube root, and the log. Some complex methods have been developed to deter ...
Data Mining: An Overview
... “A data mining algorithm is a well-defined procedure that takes data as input and produces output in the form of models or patterns” Hand, Mannila, and Smyth ...
... “A data mining algorithm is a well-defined procedure that takes data as input and produces output in the form of models or patterns” Hand, Mannila, and Smyth ...
Data Mining Tutorial
... • Sunday football highlights always look good! • If he shoots enough times, even a 95% free throw shooter will miss. • Tried 49 splits, each has 5% chance of declaring significance even if there’s no relationship. ...
... • Sunday football highlights always look good! • If he shoots enough times, even a 95% free throw shooter will miss. • Tried 49 splits, each has 5% chance of declaring significance even if there’s no relationship. ...
4.3
... Influential observations typically exist when the point is large relative to its X value. ...
... Influential observations typically exist when the point is large relative to its X value. ...
Spatial OLAP for ArcGIS Desktop
... • Number of employees • Number of parking spaces Trade area attributes: • Demographic variables like income, age, educational obtainment, ethnicity • Intersections with competitors ...
... • Number of employees • Number of parking spaces Trade area attributes: • Demographic variables like income, age, educational obtainment, ethnicity • Intersections with competitors ...
Find the Best Prospects for a New Product by Using a Data Mining Model
... This paper will introduce how to build up a data mining model using SAS Enterprise Miner, how to assess model performance, and how to validate a model by targeting the 1000 best customers for a new product. ...
... This paper will introduce how to build up a data mining model using SAS Enterprise Miner, how to assess model performance, and how to validate a model by targeting the 1000 best customers for a new product. ...