Stack Overflow
Stack Overflow

Questions tagged [multilabel-classification]

Multi-label classification refers to the problem in Machine Learning of assigning multiple target labels to each sample, where the labels represent a property of the sample point and need not be mutually exclusive.

844 questions
0
votes
0 answers

Single label train set to produce a multilabel output scikit-learn one vs rest

I was wondering whether it is possible, to use a single label train-set to produce a multilabel output. Using the modified the scikit learn example below. The train set contains a number of sentences, either labelled London or NY. At the moment,…
ulrich
  • 3,547
  • 5
  • 35
  • 49
0
votes
1 answer

Explanation for coverage_error metric in scikit learn

I am not understanding how the coverage_error is calculated in scikit learn, available in sklearn.metrics module. Explanation in the docs is as below: The coverage_error function computes the average number of labels that have to be included in the…
Joswin K J
  • 690
  • 1
  • 7
  • 16
0
votes
1 answer

Multiclass classification with Random Forest in Apache Spark

The Apache Spark's documentation (1.4.0) promises that Random Forest (the same promise is for decision trees) can be extended to multiclass classification setting. However, I can't find any way to reach this using RandomForestModel API:…
Nikita Zhiltsov
  • 654
  • 9
  • 15
0
votes
1 answer

Interpretation of Java-ML results for multi-class classification

My understanding of classification accuracy always was "#correctly classified instances divided by #instances". Using Java-ML and applying LibSVM to a multi-label problem I get accuracies (and other measurements) for every CLASS. I can't figure out…
pscl
  • 3
  • 1
0
votes
1 answer

multi class naive bayes

I don't have much experience in the data mining. My question is about the multi-class naive bayes classification . I need a simple example in this field if I want to implement this algorithm on 3 lable input and 3 output classes. My other question…
mahsa
  • 17
  • 1
  • 7
0
votes
2 answers

Multi-label classification involving range of numbers as labels

I have a classification problem where my labels are ratings, 0 - 100, with increments of 1 (e.g. 1, 2, 3, 4,). I have a data set where each row has a name, text corpus, and a rating (0 - 100). From the text corpus I am trying to extract features…
jeffrey
  • 3,196
  • 7
  • 26
  • 44
0
votes
1 answer

Limitations of multi-label classification with dynamic class set

I have a problem statement in hand and I need to know whether it can be solved by machine learning or not. It goes like this :- I have a system in which a user can upload documents, so let's say we have a file named xxxZxxx.xxx User goes multiple…
divyenduz
  • 2,037
  • 19
  • 38
0
votes
1 answer

Test Data Prediction Error in SciPy sparse matrix

I input data in LIBSVM format like this into a SciPy sparse matrix. The training set is multi-label and multi-class as described in this question I asked: Understanding format of data in scikit-learn from sklearn.datasets import…
Sasha
  • 492
  • 2
  • 6
  • 21
0
votes
1 answer

Why does multiclass Logistic Regression give different results than choosing the most probable label in a OvR classifier?

I noticed that my f-scores are slightly lower when using SK-learn's LogisticRegression classifier in conjunction with the following one-vs-rest classifier than using it by itself to do multi-class classification. class…
Nathan Breit
  • 1,661
  • 13
  • 33
0
votes
1 answer

heterogeneous class recognition with ANN / MLP

I have put together a classifying 3 layer artificial neural network that appears to work on other datasets. Playing around some artificial datasets that I made, I was unable to correctly predict between two classes when one class was positive in one…
user2368936
  • 101
  • 1
-1
votes
0 answers

why does neural network predict (softmax) 0.25?

My task is classfication with neural net. Input dimension is 4 and outputs are 4 layers. And each output dim is 4 (4 classes for each output). This is the input data They are normalized. [0.7502, 0.1567, 0.1063, 0.8041], [0.5052,…
Kenta
  • 1
-1
votes
1 answer

Fit Error OneVsOneClassifier, OneVsRestClassifier Logistic Regression for digits recognition multilabel classifier model fit error

Problem New error on problem: UserWarning: X has feature names, but LogisticRegression was fitted without feature names warnings.warn(UserWarning: X has feature names, but LogisticRegression was fitted without feature names Goal is to use…
manager_matt
  • 395
  • 4
  • 19
-1
votes
1 answer

Transforming a data frame such that labels in a row are converted to column and aggregated

I need to get my data in a specific representation for a multi label classification. I have a df such that : Key Name Description Label 1 Self service We want self service. Performance 1 Self service We want…
ayukum
  • 11
  • 1
-1
votes
1 answer

Get dependant probabilities in multiclassification

After training my CatBoostClassifier model I call get_proba function which returns me list of probabilities. The problem starts from an another point... I transfer that data into dataframe then to Excel after what I sum all float numbers in my list…
Master_Sniffer
  • 40
  • 4
-1
votes
1 answer

Is there any possibilities to directly get your predictions in float value instead of exponential value?

I am using 'sigmoid' activation function for multilabel classification and 'binary_crossentropy' enter code here img2 = img1/255 img3 = np.expand_dims(img2, axis=0) ys_ = model.predict(img3)[0] print('prediction',ys_)
Dhruvi Raval
  • 1
  • 1
1 2 3
…
56 57