Problem Set 1 K-nearest Neighbor Classification
نویسنده
چکیده
In this part, you will implement k-Nearest Neighbor (k-NN) algorithm on the 8scenes category dataset of Oliva and Torralba [1]. You are given a total of 800 labeled training images (containing 100 images for each class) and 1888 unlabeled testing images. Figure 1 shows some sample images from the data set. Your task is to analyze the performance of k-NN algorithm in classifying photographs into one of those classes. Each image is represented with a 512-dimensional GIST descriptor [2].
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