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What machine learning API does PySpark provide?

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Just like Apache Spark, PySpark also provides a machine learning API known as MLlib. MLlib supports the following types of machine learning algorithms:

  • mllib.classification: This machine learning API supports different methods for binary or multiclass classification and regression analysis such as Random Forest, Decision Tree, Naive Bayes, etc.
  • mllib.clustering: This machine learning API solves clustering problems for grouping entities subsets with one another depending on similarity.
  • mllib.fpm: FPM stands for Frequent Pattern Matching in this machine learning API. This machine learning API is used to mine frequent items, subsequences, or other structures that are used for analyzing large datasets.
  • mllib.linalg: This machine learning API is used to solve problems on linear algebra.
  • mllib.recommendation: This machine learning API is used for collaborative filtering and recommender systems.
  • spark.mllib: This machine learning API is used to support model-based collaborative filtering where small latent factors are identified using the Alternating Least Squares (ALS) algorithm used for predicting missing entries.
  • mllib.regression: This machine learning API solves problems by using regression algorithms that find relationships and variable dependencies.

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