classification Questions
2
For the last two weeks I have been in search of a mapping/crosswalk between Global Industry Classification Standard (GICS) and North American Industry Classification Standard (NAICS) and have found...
Qnp asked 22/3, 2018 at 20:12
4
Solved
For example: If I want to train a classifier (maybe SVM), how many sample do I need to collect? Is there a measure method for this?
Bobo asked 15/7, 2014 at 8:3
3
Solved
When passing x,y in fit, I am getting the following error:
Traceback (most recent call last):
File "C:/Classify/classifier.py", line 95, in
train_avg, test_avg, cms = train_model(X, y, "cep...
Calycine asked 24/11, 2016 at 7:12
20
I'm doing a multiclass text classification in Scikit-Learn. The dataset is being trained using the Multinomial Naive Bayes classifier having hundreds of labels. Here's an extract from the Scikit Le...
Osteomalacia asked 23/9, 2016 at 13:45
4
Solved
Is it possible to get classification report from cross_val_score through some workaround? I'm using nested cross-validation and I can get various scores here for a model, however, I would like to s...
Downey asked 2/3, 2017 at 17:33
5
Solved
I know that logistic regression is for binary classification and softmax regression for multi-class problem. Would it be any differences if I train several logistic regression models with the same ...
Toadinthehole asked 17/3, 2016 at 4:8
4
Solved
In a multilabel classification setting, sklearn.metrics.accuracy_score only computes the subset accuracy (3): i.e. the set of labels predicted for a sample must exactly match the corresponding set ...
Pragmatist asked 27/8, 2015 at 2:10
9
I've trained dataset using XGB Classifier, but I got this error in local. It worked on Colab and also my friends don't have any problem with same code.
I don't know what that error means...
Invalid...
Enyo asked 25/4, 2022 at 8:32
7
Solved
How do I save a trained Naive Bayes classifier to disk and use it to predict data?
I have the following sample program from the scikit-learn website:
from sklearn import datasets
iris = datasets....
Hoar asked 15/5, 2012 at 0:6
3
Solved
What is the need for setting steps_per_epoch value when calling the function fit_generator() when ideally it should be number of total samples/ batch size?
Easing asked 21/12, 2017 at 15:46
3
Solved
I have written a simple function where I am using the average_precision_score from scikit-learn to compute average precision.
My Code:
def compute_average_precision(predictions, gold):
gold_predic...
Mawson asked 10/6, 2017 at 0:4
4
Solved
I'm currently using sklearn's Ridge classifier, and am looking to ensemble this classifier with classifiers from sklearn and other libraries. In order to do this, it would be ideal to extract the p...
Serilda asked 20/3, 2014 at 15:43
5
Solved
I have a scenario where I have several thousand instances of data. The data itself is represented as a single integer value. I want to be able to detect when an instance is an extreme outlier.
Fo...
Schrick asked 20/2, 2010 at 20:5
6
Solved
I am using the LogisticRegression() method in scikit-learn on a highly unbalanced data set. I have even turned the class_weight feature to auto.
I know that in Logistic Regression it should be pos...
Interlinear asked 25/2, 2015 at 10:11
5
Solved
The classifier script I wrote is working fine and recently added weight balancing to the fitting. Since I added the weight estimate function using 'sklearn' library I get the following error :
comp...
Jurado asked 31/10, 2021 at 4:13
5
Solved
This is a simple example of a classification_report in sklearn:
from sklearn.metrics import classification_report
y_true = [0, 1, 2, 2, 2]
y_pred = [0, 0, 2, 2, 1]
target_names = ['class 0', 'class...
Joy asked 24/1, 2018 at 8:27
3
Solved
I am aware of the concept of Precision as well as the concept of Recall. But I am finding it very hard to understand the idea of a 'threshold' which makes any P-R curve possible.
Imagine I have a...
Heer asked 14/9, 2017 at 17:3
9
Solved
I'm trying to train a classifier via PyTorch. However, I am experiencing problems with training when I feed the model with training data.
I get this error on y_pred = model(X_trainTensor):
Runti...
Iago asked 24/6, 2019 at 17:5
3
Solved
I have class imbalance problem and want to solve this using cost sensitive learning.
under sample and over sample
give weights to class to use a modified loss function
Question
Scikit lear...
Hoang asked 10/9, 2015 at 3:17
2
Solved
I've been doing some research on compression-based text classification and I'm trying to figure out a way of storing a dictionary built by the encoder (on a training file) for use to run 'staticall...
Marciamarciano asked 8/3, 2013 at 13:26
10
Solved
I was trying to plot train and test learning curve in keras, however, the following code produces KeyError: 'val_acc error.
The official document <https://keras.io/callbacks/> states that in...
Ricker asked 5/10, 2016 at 18:31
3
I am writing an ETL script in Python that gets data in CSV files, validates and sanitizes the data as well as categorizes or classifies each row according to some rules, and finally loads it into a...
Deedeeann asked 8/3, 2012 at 19:45
11
I've trained a tree model with R caret. I'm now trying to generate a confusion matrix and keep getting the following error:
Error in confusionMatrix.default(predictionsTree, testdata$catgeory)
...
Thankyou asked 17/7, 2014 at 10:44
10
Solved
I'm trying to use deep learning to predict income from 15 self reported attributes from a dating site.
We're getting rather odd results, where our validation data is getting better accuracy ...
Allianora asked 15/5, 2017 at 12:22
6
Solved
I'm working on a classification problem with unbalanced classes (5% 1's). I want to predict the class, not the probability.
In a binary classification problem, is scikit's classifier.predict() usin...
Handle asked 14/11, 2013 at 18:0
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