I have a binary classification problem. I’ve been using cross validation to optimize the ElasticNet parameters. However ElasticNet only seems to work when I supply roc_auc as the scoring method to be used during CV, However I also want to test out a wide range of scoring methods, in particular accuracy. Specifically, when using accuracy, ElasticNet returns this error: However
Tag: scikit-learn
I get the same output for a classifier algorithm with sklearn and pandas
Problem I get the same output everytime regardless of the input. Context I have a .csv with IDs that represent a team of 5 persons (previously formed teams) like this: My goal with the following code is to be able to input 4 IDs and get a prediction of what the 5th member should be. Answer Mainstream statistical machine learning
do i need to use exactly same attribute names to properties in custom preprocessing class which inherit scikit learn BaseEstimator?
when writing custom classes inherit from BaseEstimator of the sklearn throwing AttributeError: object has no attribute . but that attribute is present and has values. print(null) execute or null. then it throws the above attribute error. traceback shows that this error happens in getattr() in sklearn base. I found that this is caused by attributes that assign to different property
IndexError: tuple index out of range in LabelEncoder Sklearn
I would like to train a DecisionTree using sklearn Pipeline. My goal is to predict the ‘language’ column, using the ‘tweet’ as ngram transformed features. However I am not able to make the LabelEncoder transformation works for the ‘language’ column inside a pipeline. I saw that there is a common error, but also if I try the suggested method to
How to use pytest fixture with fixture factory?
In scikit-learn, there is a function parametrize_with_checks() that is used as a pytest fixture factory–it returns a pytest.mark.parametrize fixture, and is called as a decorator with an iterable of estimators, e.g. My issue is that my list of estimators may change (or I may have multiple lists), and each list I am setting up in a fixture. Here is a
How to make dotted line in a binary array
how to create the dotted line in the below NumPy array bh=make_figure(b,’gh’) requirement: how to convert element 1 into 0 with the step of two expected outputs is like I tried with a brute force algorithm, but I am not able to find the solution output array looks like for visual representation like making a dotted line Answer Here’s one
AttributeError: ‘numpy.ndarray’ object has no attribute
I am applying selectKbest feature selection technique but it is giving me the following error: here is the portion of my code: (Note: the original data is in CSV format) Answer X is a numpy array, and you can only call the .columns method on a dataframe. You need to convert to a dataframe first, then call the method.
How to Merge arrays generated from the for loop
for a example: I have array a my current code Current output: Required output: 1)If i return the variable border in the above function it onlx gives the value of first array, so its returns both the arrays with print function. 2)How to combine both the array like mentioned below expected ouput Answer You could use an array to collect
How can we make a prediction using Scikit-Learn Classifiers?
I can easily train and test a classifier using the code below. Now, how can I make a prediction of the target variable (dependent variable) based on the independent variables? Something like this should work, I think, but it doesn’t… If we leave numerics as numerics, and put quotes around labels, I would like to predict the dependent variable, but
How to perform scikit learn’s test-train split for a 2D input?
This is a beginner level question on scikit learn’s test-train split module. I am working trying to feed in 2 inputs to the input layer of my neural network, but I am not able to get the input matrix’s dimensions correct! What change I should implement to get this working! X1 and X2 are my inputs and y is my