fix spelling mistake (#1584)
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@ -20,7 +20,7 @@ The prediction value can have different interpretations, depending on the task,
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For example, it can be logistic transformed to get the probability of positive class in logistic regression, and it can also be used as a ranking score when we want to rank the outputs.
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For example, it can be logistic transformed to get the probability of positive class in logistic regression, and it can also be used as a ranking score when we want to rank the outputs.
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The ***parameters*** are the undetermined part that we need to learn from data. In linear regression problems, the parameters are the coefficients ``$ \theta $``.
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The ***parameters*** are the undetermined part that we need to learn from data. In linear regression problems, the parameters are the coefficients ``$ \theta $``.
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Usually we will use ``$ \theta $`` to denote the parameters (there are many paramters in a model, our definition here is sloppy).
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Usually we will use ``$ \theta $`` to denote the parameters (there are many parameters in a model, our definition here is sloppy).
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### Objective Function : Training Loss + Regularization
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### Objective Function : Training Loss + Regularization
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