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Do you know any algorithms and methods that may be successful in image classification? I've read about some combined method using SVM and deep learning, however, I would like to know whether is it possible also to utilize any advantages from approaches other than deep learning.

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    $\begingroup$ What about Decision trees? $\endgroup$ – Rrz0 Nov 25 '18 at 14:04
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Support Vector Machines

Support vector machines are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis. Please note that the SVM is a machine learning algorithm and not deep learning. It can be used for image classification.

Advantages:

  1. It provides a good generalization capability.
  2. Reduction in computational complexity.
  3. It gains flexibility in the choice of the form of the threshold.

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Decision trees

Decision trees have influenced a wide area of machine learning, covering both classification and regression.

A decision tree is drawn upside down with its root at the top. The end of the branch that doesn’t split anymore is the decision/leaf, the classification step.

Advantages:

  1. 1.Can handle non parametric training data.
  2. Does not require extensive design and training.
  3. Simple and computational efficiency is good.

enter image description here

It can be seen that the decision tree above may be utilized for image classification.

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