¡@
python Programming Glossary: regressionPython Pandas: how to turn a DataFrame with “factors” into a design matrix for linear regression? http://stackoverflow.com/questions/10196860/python-pandas-how-to-turn-a-dataframe-with-factors-into-a-design-matrix-for-l with &ldquo factors&rdquo into a design matrix for linear regression If memory servies me in R there is a data type called factor.. be automatically unpacked into the necessary columns of a regression design matrix. For example a factor containing True False Maybe.. 1 0 0 0 1 0 or 0 0 1 for the purpose of using lower level regression code. Is there a way to achieve something similar using the..
Multivariate polynomial regression with numpy http://stackoverflow.com/questions/10988082/multivariate-polynomial-regression-with-numpy polynomial regression with numpy I have many samples y_i a_i b_i c_i where y is presumed.. somewhere in the Python ecosystem python numpy statistics regression share improve this question I've posted code here to solve..
How does sklearn.svm.svc's function predict_proba() work internally? http://stackoverflow.com/questions/15111408/how-does-sklearn-svm-svcs-function-predict-proba-work-internally sigmoid in this definition the same function that logistic regression and neural nets use for turning decision functions into probability..
Python: is using “..%(var)s..” % locals() a good practice? http://stackoverflow.com/questions/1550479/python-is-using-vars-locals-a-good-practice locale and preferences If you have superb integration regression testing the breakage will be caught before the beta release..
Machine Learning Algorithm for Predicting Order of Events? http://stackoverflow.com/questions/2524608/machine-learning-algorithm-for-predicting-order-of-events a function approximator e.g. neural network or linear regression to map the first n 1 parts of that window onto the nth part...
Dimension Reduction in Categorical Data with missing values http://stackoverflow.com/questions/2837850/dimension-reduction-in-categorical-data-with-missing-values in Categorical Data with missing values I have a regression model in which the dependent variable is continuous but ninety.. of the key tasks is dimension reduction before running the regression. While I am aware of several methods for dimension reduction..
Classifying Documents into Categories http://stackoverflow.com/questions/3113428/classifying-documents-into-categories is not good enough then you should try to train a logistic regression model using a L1 penalty as explained in this example of scikit.. by @ephes . The vectors used to train your logistic regression model should be the previously introduced TD log 1 IDF vectors..
How to do exponential and logarithmic curve fitting in Python? I found only polynomial fitting http://stackoverflow.com/questions/3433486/how-to-do-exponential-and-logarithmic-curve-fitting-in-python-i-found-only-poly it otherwise python numpy scipy curve fitting linear regression share improve this question For fitting y A B log x just..
How to create a simple Gradient Descent algorithm http://stackoverflow.com/questions/3837692/how-to-create-a-simple-gradient-descent-algorithm #bedrooms 3 Price 1000 s 400 i'm trying to do a simple regression using the gradient descent method but my algorithm won't work.....
How do I calculate r-squared using Python and Numpy? http://stackoverflow.com/questions/893657/how-do-i-calculate-r-squared-using-python-and-numpy From the numpy.polyfit documentation it is fitting linear regression. Specifically numpy.polyfit with degree 'd' fits a linear regression.. Specifically numpy.polyfit with degree 'd' fits a linear regression with the mean function E y x p_d x d p_ d 1 x d 1 ... p_1 x.. the R squared for that fit. The wikipedia page on linear regression gives full details. You are interested in R^2 which you can..
|