Book My Show Interview Question | Algorithm Selection

Question

You will be aware of several algorithms. But how will you decide which machine learning algorithm to choose for your classifications problem?

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Dhruv2301 55 years 1 Answer 700 views Great Grand Master 0

Answer ( 1 )

  1. swap007
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    Support Vector Machines
    – when Feature to row ratio is very high
    – There are lots of outliers in data – as it considers the points very close to the classifier,
    outliers are kind of ignored
    Random Forest and Decision Trees
    – when you are interested in significance of predictors
    – You need a quick benchmark model.
    – If you have messy data such as missing values, you don’t need to perform one-hot encoding,
    Random forests handles missing values by itself.
    Multi-layer Perceptron
    – When performance is the only thing that matters.
    – When control over the training process is very important.
    Logistic Regression
    – When impact of each predictor on the target variable is required.
    – When interpretability is more important than accuracy.
    XGBoost
    – Probably one of the best performing models currently.
    – when datasets are huge and training needs to be done quickly, parallel construction
    of trees helps in reducing the training time significantly.
    – Several hyperparametres can be tuned to get the best results out of the model.

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