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Data Science
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JJJohn
  • Member for 6 years, 8 months
  • Last seen more than 2 years ago
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Why does putting a 1/2 in front of the squared error make the math easier?
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It seem that the textbook "Machine Learning - A Probabilistic Perspective" uses input and output in a opposite way, is it?
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Could anyone explain these terms, "input space", "feature space", "sample space", "hypothesis space", "parameter space" with a concrete example?
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What does big O mean in KNN optimal weights?
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What does big O mean in KNN optimal weights?
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What does big O mean in KNN optimal weights?
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What does big O mean in KNN optimal weights?
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What does big O mean in KNN optimal weights?
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What does big O mean in KNN optimal weights?
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What is a color blob? Is it possible to use clustering algorithm to color blob detection problem?