I have this decision tree, which I would like to extract every branch from it. The image is a portion of the tree, since the original tree is much bigger but it doesn’t fit well on a single image. I’m not trying to print the rules of the tree like or like: What I’m trying to achieve is somet…
Tag: scikit-learn
Isolation forest with multiple features detecting everything as an anomaly
I have an isolation forest implementation where I take the features (all are numerical); scale them to be between 0 and 1 Then call predict: In this instance, I have 23 numerical features. When I run the script, it returns 1 for absolutely every result. When I limit the feature set to 2 columns, it returns a …
Do Machine Learning Algorithms read data top-down or bottom up?
I’m new to Machine Learning and I’m a bit confused about how data is being read for the training/testing process. Assuming my data works with date and I want the model to read the later dates first before getting to the newer dates, the data is saved in the form of earliest date on line 1 and line…
xlearn predictions error give a different mse than output by the function
the xlearn predict function gives a different mse than what you get by looking at the predictions and calculating it yourself. Here is code to do this; you can run it by cloning the xlearn repository and copying the below code in demo/regression/house_price in the repository If you save it as min_eg.py, run i…
Variability/randomness of Support Vector Machine model scores in Python’s scikitlearn
I am testing several ML classification models, in this case Support Vector Machines. I have basic knowledge about the SVM algorithm and how it works. I am using the built-in breast cancer dataset from scikit learn. Using the code below: When printing the scores as in: When I run this code, I get certain score…
Scikit-learn: Confused between coefficient of X0 and intercept
I have an extra column in my train/test set for feature/X which is just 1, this is supposed to be the coefficient for Xo, which is never in the dataset. It is mentioned to be θo in the equation; Now coming to the intercept, as a model parameter, I always knew this to be θ0. So I am a little
Different output while using fit_transform vs fit and transform from sklearn
The following code snippet illustrates the issue: Can someone explain as to why the first output is not zero and the second output is? Answer Using this works: Apparently svd_solver = ‘random’ (which is what ‘auto’ defaults to) has enough process difference between .fit(X).transform(X)…
cannot import name ‘delayed’ from ‘sklearn.utils.fixes’
How should the cannot import name ‘delayed’ from ‘sklearn.utils.fixes be solved? I have already updated sklearn and upgraded conda as well. Answer After the installation via pip install delayed and then restarting the kernel, the problem was solved.
`sklearn` asking for eval dataset when there is one
I am working on Stacking Regressor from sklearn and I used lightgbm to train my model. My lightgbm model has an early stopping option and I have used eval dataset and metric for this. When it feeds into the StackingRegressor, I saw this error ValueError: For early stopping, at least one dataset and eval metri…
Estimate a linear trend in every row across multiple columns in order to project the next value
I have five columns of historic data which I’d like to find a linear trend across the columns in every row to project the next value in year 2021/22. The historic data is stored in a data frame as follows: – Index 2016/17 2017/18 2018/19 2019/20 2020/21 0 14.53 13.75 13.03 16.05 15.15 1 14.52 13.7…