Introduction to Data Mining - ugweb.cs.ualberta.ca
... • Objective vs. subjective interestingness measures: – Objective: based on statistics and structures of patterns, e.g., support, confidence, lift, correlation coefficient etc. – Subjective: based on user’s beliefs in the data, e.g., unexpectedness, novelty, etc. ...
... • Objective vs. subjective interestingness measures: – Objective: based on statistics and structures of patterns, e.g., support, confidence, lift, correlation coefficient etc. – Subjective: based on user’s beliefs in the data, e.g., unexpectedness, novelty, etc. ...
Data Sets and Data Mining
... • Move a border element from one bin to next when that reduces the sum of all distances from each number to the mean or mode of the assigned bin ...
... • Move a border element from one bin to next when that reduces the sum of all distances from each number to the mean or mode of the assigned bin ...
Email Data Cleaning
... (2) We propose to conduct email cleaning in a ‘cascaded’ fashion. In this approach, we clean up an email by running several passes: first at email body level (non-text filtering), and then at paragraph, sentence, and word levels (text normalization). (3) It turns out that some of the tasks in the ap ...
... (2) We propose to conduct email cleaning in a ‘cascaded’ fashion. In this approach, we clean up an email by running several passes: first at email body level (non-text filtering), and then at paragraph, sentence, and word levels (text normalization). (3) It turns out that some of the tasks in the ap ...
BIOINFORMATICS Genetic network inference: from co-expression clustering to reverse engineering Patrik D’haeseleer
... used, as well as a few classical clustering methods which have not yet been adopted in gene expression analysis. We should caution the reader that different clustering methods can have very different results (see for example Figure 2), and—at this point—it is not yet clear which clustering methods a ...
... used, as well as a few classical clustering methods which have not yet been adopted in gene expression analysis. We should caution the reader that different clustering methods can have very different results (see for example Figure 2), and—at this point—it is not yet clear which clustering methods a ...
Full-Text
... data and how to physically place data on a disk. It can be used to cluster attributes based on usage and then perform logical or physical design accordingly ...
... data and how to physically place data on a disk. It can be used to cluster attributes based on usage and then perform logical or physical design accordingly ...
Initial Description of Data Mining in Business
... upon the identification of products that the same customer is likely to want. For instance, if you are interested in cold medicine, you probably are interested in tissues. Thus, it would make marketing sense to locate both items within easy reach of the other. Cross-selling is a related concept. The ...
... upon the identification of products that the same customer is likely to want. For instance, if you are interested in cold medicine, you probably are interested in tissues. Thus, it would make marketing sense to locate both items within easy reach of the other. Cross-selling is a related concept. The ...
Data Mining - School of Computer Science and Software Engineering
... Relational databases are passive data repositories in the sense that a query only shows you what is stored in the database, but cannot tell you much about the meaning or trend of the data. March 2, ...
... Relational databases are passive data repositories in the sense that a query only shows you what is stored in the database, but cannot tell you much about the meaning or trend of the data. March 2, ...
HCLS$$WWW2008$tyu
... • Reasoning capability such as sub-classing, transitive property can then be implemented at the semantic layer to increase the query expressiveness so as to retrieve more complete answers. • Allows for more advanced data analysis and integrative knowledge discovery based on the huge web of data. ...
... • Reasoning capability such as sub-classing, transitive property can then be implemented at the semantic layer to increase the query expressiveness so as to retrieve more complete answers. • Allows for more advanced data analysis and integrative knowledge discovery based on the huge web of data. ...
DecisionTrees
... the number in parentheses indicates how many records from the training dataset were classified into this bin. Some leaf nodes indicate a single data item. In real applications, it may be unwise to permit the tree to branch based on a single training item because we expect the data to have some noise ...
... the number in parentheses indicates how many records from the training dataset were classified into this bin. Some leaf nodes indicate a single data item. In real applications, it may be unwise to permit the tree to branch based on a single training item because we expect the data to have some noise ...
Data Mining Unit 1 - cse652fall2014
... • Goal: previously unseen records should be assigned a class as accurately as possible. – A test set is used to determine the accuracy of the model. Usually, the given data set is divided into training and test sets, with training set used to build the model and test set used to validate it. ...
... • Goal: previously unseen records should be assigned a class as accurately as possible. – A test set is used to determine the accuracy of the model. Usually, the given data set is divided into training and test sets, with training set used to build the model and test set used to validate it. ...
Data and Meta Data Alignment - UMIACS
... Limitations of Static Methods Monge and Elkan, “The Field Matching Problem: ...
... Limitations of Static Methods Monge and Elkan, “The Field Matching Problem: ...
i k - 淡江大學
... • the confidence of rule A B can be easily derived from the support counts of A and A B. • once the support counts of A, B, and A B are found, it is straightforward to derive the corresponding association rules AB and BA and check whether they are strong. • Thus the problem of mining associa ...
... • the confidence of rule A B can be easily derived from the support counts of A and A B. • once the support counts of A, B, and A B are found, it is straightforward to derive the corresponding association rules AB and BA and check whether they are strong. • Thus the problem of mining associa ...
MoveMine 2.0: Mining Object Relationships from Movement Data
... capuchin monkeys with tracking time from 11/10/2004 to 04/18/2005. The average sampling rate for this dataset is about 15 minutes. The monkeys form six different groups. To detect attraction and avoidance relationship pattern, a user can select corresponding method in the dropdown menu and specify p ...
... capuchin monkeys with tracking time from 11/10/2004 to 04/18/2005. The average sampling rate for this dataset is about 15 minutes. The monkeys form six different groups. To detect attraction and avoidance relationship pattern, a user can select corresponding method in the dropdown menu and specify p ...
Statistics, Data Mining, Big Data, Data Science
... TB. One computer reads with a speed of 30-35 MB/sec from disk. It will need aprox 4 months to read the web. It will be necessary aprox 1000 hard drives to read the web It will be necessary even more than that to analyze the data Today a standard architecture for such problems is being used. It consi ...
... TB. One computer reads with a speed of 30-35 MB/sec from disk. It will need aprox 4 months to read the web. It will be necessary aprox 1000 hard drives to read the web It will be necessary even more than that to analyze the data Today a standard architecture for such problems is being used. It consi ...
An Approachable Analytical Study on Big Educational Data Mining
... likely product a consumer would like, notable examples are Netflix, Amazon. The same concept is now being applied to various e-learning systems for example Edmodo is a free open source LMS that is able to predict similar books or resources based on the learner’s web activity on the e-LMS [7]. New ap ...
... likely product a consumer would like, notable examples are Netflix, Amazon. The same concept is now being applied to various e-learning systems for example Edmodo is a free open source LMS that is able to predict similar books or resources based on the learner’s web activity on the e-LMS [7]. New ap ...
Querying Graph Databases with XPath
... whether XPath-like languages can achieve the right balance of expressiveness and complexity of query evaluation in the context of graph databases. This is the question we address in this paper. There appear to be two ways to use XPath as a graph database language. The first possibility is to essenti ...
... whether XPath-like languages can achieve the right balance of expressiveness and complexity of query evaluation in the context of graph databases. This is the question we address in this paper. There appear to be two ways to use XPath as a graph database language. The first possibility is to essenti ...
Cluster Ensembles for High Dimensional Clustering
... ensembles. An possible explanation is that the features of the high dimensional data sets studied are highly redundant—applying PCA to subsampled data leads to very similar projection directions. In light of the similar behavior of the two approaches, we will focus on PCASS in our future discussion. ...
... ensembles. An possible explanation is that the features of the high dimensional data sets studied are highly redundant—applying PCA to subsampled data leads to very similar projection directions. In light of the similar behavior of the two approaches, we will focus on PCASS in our future discussion. ...
Cost-sensitive boosting for classification of imbalanced data
... • Imbalanced class distribution: The imbalance degree of a class distribution can be denoted by the ratio of the sample size of the small class to that of the prevalent class. In practical applications, the ratio can be as drastic as 1:100, 1:1000, or even larger [1]. In Ref. [33], research was cond ...
... • Imbalanced class distribution: The imbalance degree of a class distribution can be denoted by the ratio of the sample size of the small class to that of the prevalent class. In practical applications, the ratio can be as drastic as 1:100, 1:1000, or even larger [1]. In Ref. [33], research was cond ...
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.