KDnuggets New Poll: Which methods/algorithms you used for a Data Science or Machine Learning application?

Which methods/approaches you used in the past 12 months for an actual __data Science or Machine Learning-related application?

Please vote and also select your employment type below.

Algorithms data Science 490


We will analyze and publish the results in the week of Sep 12.

Poll
Which methods/algorithms you used in the past 12 months for an actual data Science or Machine Learning related application? (also select your employment type below)

Supervised Learning methods:
Bayesian networks
Decision Trees/Rules
K-nearest neighbors / K-means
Naive Bayes
Neural networks, "regular"
Neural networks, "Deep Learning"
Regression (Linear/Logistic)
SVM
Uplift modeling

Meta-methods:
Bagging
Boosting, including XGBoost
Ensemble methods
Random Forests

Unsupervised Learning methods:
Clustering algorithms
EM
Factor Analysis
PCA
Singular Value Decomposition
Statistics (descriptive)

Other:
Anomaly/Deviation detection
Association rules
Graph / Link / Social Network Analysis
Genetic algorithms
Optimization
Survival Analysis
Text Mining
Time series/Sequence analysis
Visualization
Other methods

Current employer:
Academia/University (Researcher)
Government/Non-profit
Industry (including self-employed)
Student
Other or unemployed


Current Results


See also a similar 2011 KDnuggets Poll
  • Algorithms for data analysis / data mining
relevant KDnuggets posts
  • The 10 Algorithms Machine Learning Engineers Need to Know
  • 10 Algorithm Categories for A.I., Big Data, and data Science
  • Top 10 data Mining Algorithms, Explained
and a classic survey paper Top 10 algorithms in data mining, 2008