Search results
Results from the WOW.Com Content Network
The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]
Dataframe may refer to: A tabular data structure common to many data processing libraries: pandas (software) § DataFrames; The Dataframe API in Apache Spark;
The non-primary key Units_Sold column of the fact table in this example represents a measure or metric that can be used in calculations and analysis. The non-primary key columns of the dimension tables represent additional attributes of the dimensions (such as the Year of the Dim_Date dimension).
In computer science and statistics, the Jaro–Winkler similarity is a string metric measuring an edit distance between two sequences. It is a variant of the Jaro distance metric [1] (1989, Matthew A. Jaro) proposed in 1990 by William E. Winkler.
In information theory, linguistics, and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. The Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other.
The data include quantitative variables =, …, and qualitative variables =, …,.. is a quantitative variable. We note: . (,) the correlation coefficient between variables and ;; (,) the squared correlation ratio between variables and .; In the PCA of , we look for the function on (a function on assigns a value to each individual, it is the case for initial variables and principal components ...
Frame aggregation is a feature that allows communicating on a shared link or channel, typically a TDM shared channel, with a minimum time slot that for efficiency reasons benefits from filling the time slot with data, i.e. sending two or more data frames in a single transmission.
Word2vec is a group of related models that are used to produce word embeddings.These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words.