Mean partition

In this paper will introduce an algorithm, which can improve the results of data partitioning with reliability and multiple fuzzifier. This algorithm is named TSSFC. The introduced method includes three steps namely as “labeled data with FCM”, “Data transformation”, and “Semi supervised fuzzy clustering with multiple point fuzzifiers”.

10p visharma 20-10-2023 8 4   Download

Ebook "Building cloud apps with Microsoft Azure: Best practices for DevOps, data storage, high availability, and more" explains thirteen recommended patterns for cloud development. "Pattern" is used here in a broad sense to mean a recommended way to do things: how best to go about developing, designing, and coding cloud apps. These are key patterns that will help you "fall into the pit of success" if you follow them.

201p tieulangtran 28-09-2023 9 3   Download

Lecture Probability Theory - Lecture 11: Conditional Density Functions and Conditional Expected Values. In probability theory, the conditional expectation, conditional expected value, or conditional mean of a random variable is its expected value – the value it would take “on average” over an arbitrarily large number of occurrences – given that a certain set of "conditions" is known to occur. If the random variable can take on only a finite number of values, the “conditions” are that the variable can only take on a subset of those values.

18p cucngoainhan0 10-05-2022 4 1   Download

Workflows, or computational pipelines, consisting of collections of multiple linked tasks are becoming more and more popular in many scientific fields, including computational biology. For example, simulation studies, which are now a must for statistical validation of new bioinformatics methods and software, are frequently carried out using the available workflow platforms.

19p vikentucky2711 24-11-2020 14 1   Download

DNA microarrays offer motivation and hope for the simultaneous study of variations in multiple genes. Gene expression is a temporal process that allows variations in expression levels with a characterized gene function over a period of time.

17p viflorida2711 30-10-2020 17 2   Download

Bayesian clustering algorithms, in particular those utilizing Dirichlet Processes (DP), return a sample of the posterior distribution of partitions of a set. However, in many applied cases a single clustering solution is desired, requiring a ’best’ partition to be created from the posterior sample.

10p viconnecticut2711 28-10-2020 13 1   Download

Twenty lentil genotypes were taken to study the dry matter production, partitioning, and yield, under three different dates of sowing (15 November, 6 December, and 27 December), data were recorded at various growth stages. A decrease in root dry matter in late sowings at pre-flowering and post-flowering was observed. Crop grown on the second sowing (late sown, 6 December) registered higher means for total dry weight and yield at 50 and 65 days after sowing

8p nguathienthan4 21-04-2020 11 0   Download

Generation mean analysis was employed in two crosses viz., MDU 1 x Mash 114 and MDU 1 x Mash 1008 of balckgram to partition the mean into various components viz., additive, dominance and epistasis. Traits viz., number of clusters per plant, pod length, and number of seeds per pod were controlled by additive gene action in the cross MDU 1 x Mash 114. The additive as well as additive x additive type of gene action were in control of seed yield per plant, MYMV disease scores and most of yield components in the cross MDU 1 x Mash 114.

7p nguathienthan2 25-12-2019 12 1   Download

The results obtained indicate that the two algorithms are as efficient as the fuzzy k-Means algorithm when clustering numerical values. Further, on an ANOVA test, k-AMH Numeric I obtained the highest accuracy score of 0.69 for the six datasets combined with p-value less than 0.01, indicating a 95% confidence level.

13p meriday 20-04-2019 14 0   Download

Chapter 6: Unsupervised Learning – Clustering Introduction to unsupervised learning and clustering, Partitional clustering (k-Means algorithm), Hierarchical clustering, Expectation Maximization (EM) algorithm, Incremental Clustering.

48p cocacola_10 08-12-2015 38 1   Download

Sense induction seeks to automatically identify word senses directly from a corpus. A key assumption underlying previous work is that the context surrounding an ambiguous word is indicative of its meaning. Sense induction is thus typically viewed as an unsupervised clustering problem where the aim is to partition a word’s contexts into different classes, each representing a word sense.

9p bunthai_1 06-05-2013 46 2   Download

In one form or another, the phenomena associated with "meaning transfer" have become central issues in a lot of recent work on semantics. Speaking very roughly, we can partition approaches to the phenomenon along two dimensions, which yield four basic points of departure. In the first two, people have considered transfer in basically semantic or linguistic terms.

2p bunmoc_1 20-04-2013 38 1   Download

Types of Segments Segments are space-occupying objects in a database. They use space in the data files of a database. This section describes the different types of segments. Table A table is the most common means of storing data within a database. A table segment stores that data for a table that is neither clustered nor partitioned. Data within a table segment is stored in no particular order, and the database administrator (DBA) has very little control over the location of rows within the blocks in a table. All the data in a table segment must be stored in one tablespace.

34p trinh02 28-01-2013 52 3   Download

With the 4GB Gridfire , you can back up, store, carry and offload large files with one affordable, convenient device. What’s more, means no moving parts, and therefore less chance of damage if the device is dropped. 2 The 2GB One-Tech is the best choice for high-performance results from your digital camera and other handheld devices. 3 The STM gives you the ability to carry your files AND your software on a secure USB drive, by using separate partitions to … 4 The Airlink connects your desktop PC to a network, using the latest advanced silicon chip technology....

1p duongth03 13-10-2012 126 11   Download

We explore an approach to possibilistic fuzzy c-means clustering that avoids a severe drawback of the conventional approach, namely that the objective function is truly minimized only if all cluster centers are identical. Our approach is based on the idea that this undesired property can be avoided if we introduce a mutual repulsion of the clusters, so that they are forced away from each other. In our experiments we found that in this way we can combine the partitioning property of the probabilistic fuzzy c-means algorithm with the advantages of a possibilistic approach w.r.t.

7p ledung 13-03-2009 181 37   Download