Tag: classification

Python Keras ValueError: Data cardinality is ambiguous

I am attempting to make a model that can predict whether a credit card transaction was fraudulent or not. My dataset is available on Kaggle. Everything works up to when I fit my model, when I get this error: Could someone help me figure out what’s wrong? Answer The main issue with your code is that the model’s input shape

Suspect overfitting binary classification toy problem with scikit-learn RandomForestClassifier

classification machine-learning python random-forest scikit-learn

I’m trying to train a Random Forest to classify the species of a set of flowers from the iris dataset. However, the validation looks kind of weird to me, since it looks like the results are perfect, which is something I would not expect. Since I would like to perform a binary classification, I exclude from the training dataset the

Mismatch of manual computation of a evaluation metrics with Sklearn functions

classification machine-learning precision-recall python scikit-learn

I wanted to compare the manual computations of the precision and recall with scikit-learn functions. However, recall_score() and precision_score() of scikit-learn functions gave me different results. Not sure why! Could you please give me some advice why I am getting different results? Thanks! My confusion matrix: Answer It should be (check return value’s ordering): Please refer: here

Micro metrics vs macro metrics

classification python scikit-learn statistics

To test the results of my multi-label classfication model, I measured the Precision, Recall and F1 scores. I wanted to compare two different results, Micro and Macro. I have a dataset with few rows, but my label count is around 1700. Why is the macro so low even though I get a high result in micro, which one would be

AttributeError: ‘numpy.ndarray’ object has no attribute ‘self’

classification neural-network numpy python

I started implementing the backend of neural network but got stuck in a code of python. The below is the code for neural Network. While i was making use of the userdefined class in one of the application to be made, i got an error by name attributeError. Please help me out solving it. I tried all the indentation syntax

How to train Naive Bayes Classifier for n-gram (movie_reviews)

classification nlp nltk python

Below is the code of training Naive Bayes Classifier on movie_reviews dataset for unigram model. I want to train and analyze its performance by considering bigram, trigram model. How can we do it. Answer Simply change your featurizer BTW, your code will be a lot faster if you change your featurizer to do use a set for your stopword list

Getting a list of all known classes of vgg-16 in keras

classification deep-learning keras python vgg-net

I use the pre-trained VGG-16 model from Keras. My working source code so far is like this: I wound out that the model is trained on 1000 classes. It there any possibility to get the list of the classes this model is trained on? Printing out all the prediction labels is not an option because there are only 5 returned.

List of all classification algorithms [closed]

algorithm classification machine-learning python scikit-learn

Closed. This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 28 days ago. The community reviewed whether to reopen this question 28 days ago and left it closed: Original close reason(s) were not resolved Improve this

How to use if and else statements to achieve Age Classifier program

classification if-statement python

I have an assignment in my Python class. It says: Write a program that asks the user to enter a person’s age. The program should display a message indicating whether the person is an infant, child, teenager, or adult. Here are the following guidelines: If the person is 1 year old or less, he or she is an infant. If

Scikit-learn train_test_split with indices

classification python scikit-learn scipy

How do I get the original indices of the data when using train_test_split()? What I have is the following But this does not give the indices of the original data. One workaround is to add the indices to data (e.g. data = [(i, d) for i, d in enumerate(data)]) and then pass them inside train_test_split and then expand again. Are