I have some questions related to machine learning course : how can I use k-NN classification with Olivetti Faces dataset ?
Answer:-
In machine learning, we represent each data instances in a
feature space. Refer: Mark Whitfield Iris flower dataset for
example. So, each data point co-ordinates corresponds to the
feature. With this representation, you can apply KNN to any
dataset.
face recognition was performed using the face images in the Olivetti data set. The steps for face recognition are as follows:
We can classify the face recognition researches carried out with 2D face recognition approach in three categories; analytical (feature-based, local), global (appearance) and hybrid methods. While analytical approaches want to be recognized by comparing the properties of the facial components, global approaches try to achieve a recognition with data derived from all the face. Hybrid approaches, together with local and global approaches, try to obtain data that expresses the face more accurately.
Face recognition performend in this kernel can evaluated under global face recognition approaches.
In analytical approaches, the distance of the determined feature points and the angles between them, the shape of the facial features or the variables containing the regional features are obtained from the face image and the variables are used in face recognition. Analytical methods examine the face images in two different ways according to the pattern and geometrical properties. In these methods, the face image is represented by smaller size data, so the big size problem that increases the operations in face recognition is solved.
I have some questions related to machine learning course : how can I use k-NN classification...
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