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  2. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Altszyler and coauthors (2017) studied Word2vec performance in two semantic tests for different corpus size. [29] They found that Word2vec has a steep learning curve, outperforming another word-embedding technique, latent semantic analysis (LSA), when it is trained with medium to large corpus size (more than 10 million words). However, with a ...

  3. Flajolet–Martin algorithm - Wikipedia

    en.wikipedia.org/wiki/Flajolet–Martin_algorithm

    Estimate the cardinality of as /, where . The idea is that if n {\displaystyle n} is the number of distinct elements in the multiset M {\displaystyle M} , then B I T M A P [ 0 ] {\displaystyle \mathrm {BITMAP} [0]} is accessed approximately n / 2 {\displaystyle n/2} times, B I T M A P [ 1 ] {\displaystyle \mathrm {BITMAP} [1]} is accessed ...

  4. Apache Spark - Wikipedia

    en.wikipedia.org/wiki/Apache_Spark

    The Dataframe API was released as an abstraction on top of the RDD, followed by the Dataset API. In Spark 1.x, the RDD was the primary application programming interface (API), but as of Spark 2.x use of the Dataset API is encouraged [3] even though the RDD API is not deprecated. [4] [5] The RDD technology still underlies the Dataset API. [6] [7]

  5. MinHash - Wikipedia

    en.wikipedia.org/wiki/MinHash

    To estimate J(A,B) using this version of the scheme, let y be the number of hash functions for which h min (A) = h min (B), and use y/k as the estimate. This estimate is the average of k different 0-1 random variables, each of which is one when h min ( A ) = h min ( B ) and zero otherwise, and each of which is an unbiased estimator of J ( A , B ) .

  6. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    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]

  7. Estimation of covariance matrices - Wikipedia

    en.wikipedia.org/wiki/Estimation_of_covariance...

    Clearly, the difference between the unbiased estimator and the maximum likelihood estimator diminishes for large n. In the general case, the unbiased estimate of the covariance matrix provides an acceptable estimate when the data vectors in the observed data set are all complete: that is they contain no missing elements. One approach to ...

  8. Stylists Say These Are the Best Hairstyles for Women Over 60

    www.aol.com/lifestyle/youthful-celebrity...

    Forget what you thought about long hair past the age of 40—thick hair actually looks more youthful and polished when it falls shoulder-length or longer. Shorter hair has a tendency to expand at ...

  9. Estimator - Wikipedia

    en.wikipedia.org/wiki/Estimator

    In statistics, an estimator is a rule for calculating an estimate of a given quantity based on observed data: thus the rule (the estimator), the quantity of interest (the estimand) and its result (the estimate) are distinguished. [1] For example, the sample mean is a commonly used estimator of the population mean. There are point and interval ...