These algorithms can be applied to almost any data problem:
- Linear Regression.
- Logistic Regression.
- Decision Tree.
- SVM.
- Naive Bayes.
- KNN.
- K-Means.
- Random Forest.
Which algorithms can be parallelized?
The algorithms
- Quicksort.
- Selection sort.
- Insertion sort.
- Counting sort.
- Batcher's Bitonic Sort.
- Radix Sort.
- String Radix Sort.
Can machine learning be parallelized?
A big data machine learning appli- cation can be parallelized with different algorithms. ... One algorithm can be par- allelized by using different computation models. We present model rotation based computation model has advantages compared with other computation models (see Section III).
