Products related to Clustering:
-
Data Clustering : Algorithms and Applications
Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities.Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches.It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validationIn this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas.They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.
Price: 130.00 £ | Shipping*: 0.00 £ -
Combining DBSCAN and Grid Based Clustering For Performance Analysis
Price: 33.12 £ | Shipping*: 0.00 £ -
The Golden Palominos Clustering Train 1985 USA 12" vinyl CEL187
GOLDEN PALOMINOS Clustering Train (Rare 1985 US 4-track promo only 12 featuring 4:10 Edited Version & 6:04 Long Version both with vocals by Michael Stipe b/w Kind Of True & Silver Bullet housed in custom stickered die-cut sleeve CEL187)
Price: 20.00 € | Shipping*: 0.00 € -
Unsupervised Machine Learning for Clustering in Political and Social Research
In the age of data-driven problem-solving, applying sophisticated computational tools for explaining substantive phenomena is a valuable skill.Yet, application of methods assumes an understanding of the data, structure, and patterns that influence the broader research program.This Element offers researchers and teachers an introduction to clustering, which is a prominent class of unsupervised machine learning for exploring and understanding latent, non-random structure in data.A suite of widely used clustering techniques is covered in this Element, in addition to R code and real data to facilitate interaction with the concepts.Upon setting the stage for clustering, the following algorithms are detailed: agglomerative hierarchical clustering, k-means clustering, Gaussian mixture models, and at a higher-level, fuzzy C-means clustering, DBSCAN, and partitioning around medoids (k-medoids) clustering.
Price: 17.00 £ | Shipping*: 3.99 £
-
Where is the k-means clustering used?
K-means clustering is used in various fields such as machine learning, data mining, pattern recognition, and image analysis. It is commonly used in market segmentation, customer profiling, document clustering, and image compression. Additionally, k-means clustering is also used in biological data analysis to group genes with similar expression patterns and in social network analysis to identify communities of users with similar interests or behaviors.
-
Which topics would you most likely use in a small presentation about k-means clustering?
In a small presentation about k-means clustering, I would likely cover the following topics: 1. Introduction to clustering and the concept of unsupervised learning. 2. Explanation of the k-means algorithm, including how it works and its key components such as centroids and clusters. 3. Steps involved in implementing k-means clustering, such as selecting the number of clusters (k) and evaluating the clustering results.
-
Why have the bonds in my portfolio, which are securities, lost the most value, even though they are EU government bonds considered safe investment havens?
The value of bonds in your portfolio may have decreased due to changes in interest rates. When interest rates rise, the value of existing bonds decreases because they are paying lower interest rates than newly issued bonds. This is known as interest rate risk. Even though EU government bonds are considered safe investments, they are still subject to fluctuations in interest rates, which can impact their value. Additionally, other factors such as economic conditions, inflation expectations, and market sentiment can also affect the value of bonds in your portfolio.
-
How does investing in bonds differ from investing in a bank account?
Investing in bonds involves purchasing debt securities issued by governments or corporations, which pay a fixed interest rate over a specified period of time. In contrast, investing in a bank account typically involves depositing money into a savings or checking account, where it earns a variable interest rate set by the bank. Bonds generally offer higher potential returns than bank accounts, but they also carry a higher level of risk. Additionally, bonds have a maturity date, while bank accounts provide more immediate access to funds.
Similar search terms for Clustering:
-
Model-Based Clustering and Classification for Data Science : With Applications in R
Cluster analysis finds groups in data automatically.Most methods have been heuristic and leave open such central questions as: how many clusters are there?Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment.This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions.It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering.Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.
Price: 69.99 £ | Shipping*: 0.00 £ -
Investing in Bonds For Dummies
Improve the strength of your portfolio with this straightforward guide to bond investing Investing in Bonds For Dummies introduces you to the basics you need to know to get started with bond investing.You’ll find details on understanding bond returns and risks, and recognizing the major factors that influence bond performance.Unlike some investing vehicles, bonds typically pay interest on a regular schedule, so you can use them to provide an income stream while you protect your capital.This easy-to-understand guide will show you how to incorporate bonds into a diversified portfolio and a solid retirement plan.Learn the ins and outs of buying and selling bonds and bond fundsUnderstand the risks and potential rewards in corporate bonds, government bonds, and beyondDiversify your portfolio by using bonds to balance stocks and other investmentsGain the fundamental information you need to make smart bond investment choicesThis Dummies investing guide is great for investors looking for a resource to help them understand, evaluate, and incorporate bonds into their current investment portfolios.
Price: 14.99 £ | Shipping*: 3.99 £ -
An Introduction to Spatial Data Science with GeoDa : Volume 2: Clustering Spatial Data
This book is the second in a two-volume series that introduces the field of spatial data science.It moves beyond pure data exploration to the organization of observations into meaningful groups, i.e., spatial clustering.This constitutes an important component of so-called unsupervised learning, a major aspect of modern machine learning. The distinctive aspects of the book are both to explore ways to spatialize classic clustering methods through linked maps and graphs, as well as the explicit introduction of spatial contiguity constraints into clustering algorithms.Leveraging a large number of real-world empirical illustrations, readers will gain an understanding of the main concepts and techniques and their relative advantages and disadvantages.The book also constitutes the definitive user’s guide for these methods as implemented in the GeoDa open source software for spatial analysis. It is organized into three major parts, dealing with dimension reduction (principal components, multidimensional scaling, stochastic network embedding), classic clustering methods (hierarchical clustering, k-means, k-medians, k-medoids and spectral clustering), and spatially constrained clustering methods (both hierarchical and partitioning).It closes with an assessment of spatial and non-spatial cluster properties. The book is intended for readers interested in going beyond simple mapping of geographical data to gain insight into interesting patterns as expressed in spatial clusters of observations.Familiarity with the material in Volume 1 is assumed, especially the analysis of local spatial autocorrelation and the full range of visualization methods.
Price: 76.99 £ | Shipping*: 0.00 £ -
Moving Beyond Modern Portfolio Theory : Investing That Matters
Moving Beyond Modern Portfolio Theory: Investing That Matters tells the story of how Modern Portfolio Theory (MPT) revolutionized the investing world and the real economy, but is now showing its age.MPT has no mechanism to understand its impacts on the environmental, social and financial systems, nor any tools for investors to mitigate the havoc that systemic risks can wreck on their portfolios.It’s time for MPT to evolve. The authors propose a new imperative to improve finance’s ability to fulfil its twin main purposes: providing adequate returns to individuals and directing capital to where it is needed in the economy.They show how some of the largest investors in the world focus not on picking stocks, but on mitigating systemic risks, such as climate change and a lack of gender diversity, so as to improve the risk/return of the market as a whole, despite current theory saying that should be impossible. "Moving beyond MPT" recognizes the complex relations between investing and the systems on which capital markets rely, "Investing that matters" embraces MPT’s focus on diversification and risk adjusted return, but understands them in the context of the real economy and the total return needs of investors.Whether an investor, an MBA student, a Finance Professor or a sustainability professional, Moving Beyond Modern Portfolio Theory: Investing That Matters is thought-provoking and relevant.Its bold critique shows how the real world already is moving beyond investing orthodoxy.
Price: 36.99 £ | Shipping*: 0.00 £
-
Why have the bonds in my portfolio, which are securities, lost the most value, even though they are EU government bonds considered as safe investment havens?
The value of EU government bonds in your portfolio may have decreased due to a variety of factors such as changes in interest rates, inflation expectations, or market sentiment. Even though EU government bonds are generally considered safe investment havens, they are still subject to market fluctuations and can lose value in certain economic conditions. Additionally, global events, economic uncertainty, or changes in government policies can also impact the value of these securities. It's important to monitor the market and economic conditions to understand the reasons behind the decrease in value of your bond holdings.
-
Is it worth investing in Ukraine's war bonds?
Investing in Ukraine's war bonds can be a way to show support for the country during its conflict with Russia, but it also comes with risks. The situation in Ukraine is volatile and the outcome of the conflict is uncertain, which could affect the value of the bonds. Additionally, there may be concerns about the stability of the Ukrainian economy and the government's ability to repay the bonds. Therefore, investing in Ukraine's war bonds should be carefully considered and individuals should weigh the potential risks and rewards before making a decision.
-
Can you finance a dual study program with savings?
Yes, it is possible to finance a dual study program with savings. If you have saved up enough money to cover the costs of tuition, living expenses, and other related expenses, you can use your savings to fund your dual study program. However, it is important to carefully consider the amount of savings you have and whether it will be enough to cover all the expenses associated with the program before making a decision. Additionally, you may also want to explore other financing options such as scholarships, student loans, or part-time work to supplement your savings if needed.
-
What tasks does an investment and securities specialist have at the savings bank?
An investment and securities specialist at a savings bank is responsible for providing financial advice and guidance to clients regarding investment options and securities. They help clients make informed decisions about their investments based on their financial goals and risk tolerance. Additionally, they may assist clients in buying and selling securities, managing their investment portfolios, and staying informed about market trends and developments. Overall, their main tasks involve helping clients grow and manage their wealth through strategic investment decisions.
* All prices are inclusive of VAT and, if applicable, plus shipping costs. The offer information is based on the details provided by the respective shop and is updated through automated processes. Real-time updates do not occur, so deviations can occur in individual cases.