# Tagged Questions

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### Ensemble of models with different feature spaces

BACKGROUND I have data in which the dependent variable is binary with a highly-skewed distribution: <1% records are 1 (doers), >99% records are 0 (non-doers). I'm using logistic regression to ...
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### Solving for regression parameters in closed-form vs gradient descent

In Andrew Ng's machine learning course, he introduces linear regression and logistic regression, and shows how to fit the model parameters using gradient descent and Newton's method. I know gradient ...
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### Updating classification probability in logistic regression through time

I am building a predictive model that forecasts a student's probability of success at the end of a term. I’m specifically interested in whether the student succeeds or fails, where success is usually ...
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### Weights of radial basis function networks

If I use radial basis function networks (RBFNs) for probability estimation by plugging the output of the RBFNs into the Logistic function are weights between 0 and 1 sufficient?
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### Adjusting existing algorithm - likelihood for presence-only data

Logistic regression fits a model that predicts a binary variable whilst performing a logit transformation of the linear combination (LC) of predictors: 1/1 + exp(-LC). I have a working machine ...
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### How do I handle predictor variables from different distributions in logistic regression?

I am using logistic regression to predict y given x1 and x2: z = B0 + B1 * x1 + B2 * x2 y = e^z / (e^z + 1) How is logistic regression supposed to handle cases ...
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### Identifying culs-de-sac (circular housing arrangements) with GIS data

I'm thinking about a new project, so I don't have data yet, but I plan on collecting GIS information for houses within a state. Usually in the U.S., these dead-end streets will have a large circle ...