linear-regression
TensorFlow: “Attempting to use uninitialized value” in variable initialization
Run this: init = tf.global_variables_initializer() sess.run(init) Or (depending on the version of TF that you have): init = tf.initialize_all_variables() sess.run(init)
How to make seaborn regplot partially see through (alpha)
Use the scatter_kws argument. For example: ax = sb.regplot(x=”total_bill”, y=”tip”, data=tips, scatter_kws={‘alpha’:0.3})
Why do I get only one parameter from a statsmodels OLS fit
Try this: X = sm.add_constant(X) sm.OLS(y,X) as in the documentation: An intercept is not included by default and should be added by the user statsmodels.tools.tools.add_constant
Cost Function, Linear Regression, trying to avoid hard coding theta. Octave.
You can use vectorize of operations in Octave/Matlab. Iterate over entire vector – it is really bad idea, if your programm language let you vectorize operations. R, Octave, Matlab, Python (numpy) allow this operation. For example, you can get scalar production, if theta = (t0, t1, t2, t3) and X = (x0, x1, x2, x3) … Read more
gradient descent using python and numpy
I think your code is a bit too complicated and it needs more structure, because otherwise you’ll be lost in all equations and operations. In the end this regression boils down to four operations: Calculate the hypothesis h = X * theta Calculate the loss = h – y and maybe the squared cost (loss^2)/2m … Read more
How to get a regression summary in scikit-learn like R does?
There exists no R type regression summary report in sklearn. The main reason is that sklearn is used for predictive modelling / machine learning and the evaluation criteria are based on performance on previously unseen data (such as predictive r^2 for regression). There does exist a summary function for classification called sklearn.metrics.classification_report which calculates several … Read more