Welcome to Part 5 of our Data Science Primer. Choosing the right ML algorithm for your task can be overwhelming. There are dozens of options, each with their own advantages and disadvantages. However, rather than bombarding you with all options, we’re going to jump straight to best ...
Confidence is the probability of seeing the consequent item (a "then" term) within data, given that the data also contains the antecedent(the "if" term) item. In other words, confidence tells you: THEN How likely it is for 1 item to be purchase given that, IF another item is pu...
(Mannini & Sabatini, 2011) propose a cHMM-based sequential classifier for physical activity recognition, which is indicated to outperform the GMM classier they use for the same data (99.1% vs. 92.2%). (Kwon, Kang, & Bae, 2014) present an unsupervised learning method using a smartphone ...
Data Science An illustrated guide on essential machine learning concepts Shreya Rao February 3, 2023 6 min read Must-Know in Statistics: The Bivariate Normal Projection Explained Data Science Derivation and practical examples of this powerful concept ...
It is true that for a given data set, there exists one algorithm that does it best. But don't be satisfied with just the best single view of the pattern. The best perspective among other views nearly as poor is not sufficient to define the pattern properly. A number of different “...
In fact, when the average set size is large, the space for prefix trees is several times of space for the data itself. Although the space cost can be sharply reduced by limiting the height of the tree (e.g., LIMIT [5], ttjoin [2]), or storing the tree as several arrays (e.g...
Here we introduce Local Topological Recurrence Analysis (LoTRA), a simple computational approach for analyzing time-series data. Its versatility is elucidated using simulated data, Parkinsonian gait, and in vivo brain dynamics. We also show that this algorithm can be used to build a remarkably simp...
[Lecture Notes in Computer Science] Advanced Data Mining and Applications Volume 4093 || A Fast Algorithm for Maintenance of Association Rules in Incremental DatabasesIn this paper, we propose an algorithm for maintaining the frequent itemsets discovered in a database with minimal re-computation when...
It cannot only generate long-and short-term cues, but also adaptively select them for data association. In addition to long-term and short-term clues, the author also uses local interactive information to solve the problem of ID switch. They find that the switcher is crucial for the correct...
For point mutations in the control region and for indels in the coding region the rates were estimated from 30,141 forensic mitotypes from EMPOP by the method described in [41]. Due to the lack of sufficient forensic data for transitions and transversions in the coding region the rates were...