Sebanyak 23 item atau buku ditemukan

Data Mining

Proceedings

The Fourth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. This is reflected in the talks by the four keynote speakers who discuss data usability issues in systems for data mining in science and engineering, issues raised by new technologies that generate biological data, ways to find complex structured patterns in linked data, and advances in Bayesian inference techniques. This proceedings includes 61 research papers.

Proceedings of the 5th International Conference on Data Mining

The Fifth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. Advances in information technology and data collection methods have led to the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines. The field of data mining draws upon extensive work in areas such as statistics, machine learning, pattern recognition, databases, and high performance computing to discover interesting and previously unknown information in data. This conference results in data mining, including applications, algorithms, software, and systems.

In addition, WFIM can generate orders of magnitude fewer patterns than the
traditional weighted frequent itemset mining algorithms. To test the scalability
with the number of transactions, the TlOMDxK dataset was used. WFIM scales
much ...

Data Mining of Traffic Video Sequences

Automatically analyzing video data is extremely important for applications such as monitoring and data collection in transportation scenarios. Machine learning techniques are often employed in order to achieve these goals of mining traffic video to find interesting events. Typically, learning-based methods require significant amount of training data provided via human annotation. For instance, in order to provide training, a user can give the system images of a certain vehicle along with its respective annotation. The system then learns how to identify vehicles in the future - however, such systems usually need large amounts of training data and thereby cumbersome human effort. In this research, we propose a method for active l\earning in which the system interactively queries the human for annotation on the most informative instances. In this way, learning can be accomplished with lesser user effort without compromising performance. Our system is also efficient computationally, thus being feasible in real data mining tasks for traffic video sequences.

Machine learning techniques are often employed in order to achieve these goals of mining traffic video to find interesting events. Typically, learning-based methods require significant amount of training data provided via human annotation.

Data Mining Methods & Models

The book introduces readers to data mining methods and models, including association rules, clustering, K-nearest neighbor, statistical inference, neural networks, linear and logistic regression, and multivariate analysis. Taking a unified approach based on CRISP methodology, the book discusses the latest techniques for uncovering hidden nuggets of information and provides insight into how the data mining algorithms actually work with hands-on experience performing data mining on large data sets. · Dimension Reduction Methods · Regression Modeling · Multiple Regression and Model Building · Logistic Regression · Naïve Bayes and Bayesian Networks · Genetic Algorithms · Case Study: Modeling Response to Direct-Mail Marketing

The book introduces readers to data mining methods and models, including association rules, clustering, K-nearest neighbor, statistical inference, neural networks, linear and logistic regression, and multivariate analysis.

Data Mining: Techniques And Trends

Association rule mining (ARM) is the process of discovering interesting
relationships and associations amongst various items in databases. It primarily
concentrates on transactional databases with the objective of establishing
associations ...

Data Mining Techniques

This Book Addresses All The Major And Latest Techniques Of Data Mining And Data Warehousing. It Deals With The Latest Algorithms For Discussing Association Rules, Decision Trees, Clustering, Neural Networks And Genetic Algorithms. The Book Also Discusses The Mining Of Web Data, Temporal And Text Data. It Can Serve As A Textbook For Students Of Compuer Science, Mathematical Science And Management Science, And Also Be An Excellent Handbook For Researchers In The Area Of Data Mining And Warehousing.

This Book Addresses All The Major And Latest Techniques Of Data Mining And Data Warehousing.

Data Mining and Warehousing

Data Mining is the process of analyzing large amount of data in search of previously undiscovered business patterns. Data Warehousing is a relational/multidimensional database that is designed for Query and Analysis rather than Transaction Processing. This book provides a systematic introduction to the principles of Data Mining and Data Warehousing. It covers the entire range of data mining algorithms (prediction, classification, and association), data mining products and applications, stages.

Data Warehousing is a relational/multidimensional database that is designed for Query and Analysis rather than Transaction Processing. This book provides a systematic introduction to the principles of Data Mining and Data Warehousing.

Data Warehousing Olap And Data Mining

This Book Is Mainly Intended For It Students And Professionals To Learn Or Implement Data Warehousing Technologies. It Experiences The Real-Time Environment And Promotes Planning, Managing, Designing, Implementing, Supporting, Maintaining And Analyzing Data Warehouse In Organizations And It Also Provides Various Mining Techniques As Well As Issues In Practical Use Of Data Mining Tools.The Book Is Designed For The Target Audience Such As Specialists, Trainers And It Users. It Does Not Assume Any Special Knowledge As Background. Understanding Of Computer Use, Databases And Statistics Will Be Helpful.

Introduction 249 1.1 What is Data Mining 251 1.2 Definitions 252 1.3 Data Mining
Process 253 1.4 Data Mining Background 254 1.5 Data Mining Models 256 1.6
Data Mining Methods 257 1.7 Data Mining Problems/Issues 260 1.8 Potential ...

Bidrag til Sveriges officiela statistik ...

... Skogsodling och återväxt . . . . . . . . . . . . . . . Afdikning . . . . . . . . . . . . . . . . . . . . . .
Skogstorpsanläggningnr . . . _ . . . . . . . . . . . . Skogseldar . . . . . . . . . . . . . . . . . . . . .
Stormskador . . . . . . . . . . . . . . . . . . _ . . Skogsinsekter Öfriga skador på ... non.
encore.