Questions tagged [multiclass-classification]

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167
votes
6answers
171k views

Micro Average vs Macro average Performance in a Multiclass classification setting

I am trying out a multiclass classification setting with 3 classes. The class distribution is skewed with most of the data falling in 1 of the 3 classes. (class labels being 1,2,3, with 67.28% of the ...
24
votes
4answers
21k views

Unbalanced multiclass data with XGBoost

I have 3 classes with this distribution: Class 0: 0.1169 Class 1: 0.7668 Class 2: 0.1163 And I am using xgboost for ...
11
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2answers
8k views

Keras Multiple “Softmax” in last layer possible?

Is it possible to implement mutiple softmaxes in the last layer in Keras? So the sum of Nodes 1-4 = 1; 5-8 = 1; etc. Should I go for a different network design?
10
votes
4answers
863 views

SGDClassifier: Online Learning/partial_fit with a previously unknown label

My training set contains about 50k entries with which I do an initial learning. On a weekly basis, ~ 5k entries are added; but the same amount "disappears" (as it is user data which has to be deleted ...
10
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1answer
2k views

Text-Classification-Problem: Is Word2Vec/NN the best approach?

I am looking to design a system that given a paragraph of text will be able to categorize it and identify the context: Is trained with user generated text paragraphs (like comments/questions/answers) ...
9
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1answer
1k views

Imbalanced data causing mis-classification on multiclass dataset

I am working on text classification where I have 39 categories/classes and 8.5 million records. (In future data and categories will increase). Structure or format of my data is as follows. ...
8
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2answers
1k views

Which comes first? Multiple Imputation, Splitting into train/test, or Standardization/Normalization

I am working on a multi-class classification problem, with ~65 features and ~150K instances. 30% of features are categorical and the rest are numerical (continuous). I understand that standardization ...
8
votes
1answer
15k views

What is the best method for classification of time series data? Should I use LSTM or a different method?

I am trying to classify raw accelerometer data x,y,z to its corresponding label. What is the best architecture for best results? Or, does anyone have any suggestions on LSTM architectures built on ...
8
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3answers
8k views

Good performance metrics for multiclass classification problem besides accuracy?

I am trying to solve a multiclass classification problem. The dataset is balanced. I have been using accuracy as a performace metric till now. Are there any other good performance metrics for this ...
7
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5answers
2k views

Products classification by name

I am a beginner with machine learning, and I'm trying to build a model to classify products by category according to the words present in the product name. My goal is to predict the category of some ...
7
votes
2answers
7k views

SPARK Mllib: Multiclass logistic regression, how to get the probabilities of all classes rather than the top one?

I am using LogisticRegressionWithLBFGS to train a multi-class classifier. Is there a way to get the probability of all classes (not only the top candidate class) ...
6
votes
6answers
7k views

Deep network not able to learn imbalanced data beyond the dominant class

I have data with 5 output classes. The training data has the following no of samples for these 5 classes: [706326, 32211, 2856, 3050, 901] I am using the following keras (tf.keras) code: <...
6
votes
1answer
6k views

Multi-class classification v.s. Binary classification

If a training set has 5 classes including : "label-A", "label-B", "label-C", "label-D", "others". But the problem is much simpler, it wants to distinguish each input whether it is belongs to "label-...
6
votes
3answers
11k views

Multiple output classes in keras

I'm trying to predict movie genres using a neural network. I initially considered using a softmax layer as my output layer, but since a movie can have multiple genre labels, how should my output be? ...
6
votes
2answers
1k views

Classifier Chains

My question is about creating classifier chains The problem I am working with is a multiclass problem where I have to assign one of 7 possible classes. I started by training a single random forest ...
6
votes
1answer
922 views

How does exactly class_weight in Keras work?

I'm working on a multi-label problem in Keras, using binary-cross-entropy loss function with sigmoid activation. Let's say I have 4 classes, so a response might look like this: ...
6
votes
2answers
877 views

Earlystopping in multi-output deep learning

When working with a neural network with more than one output, what is generally advised as the best strategy for early-stopping the training process? Given that I am currently monitoring the net ...
5
votes
2answers
13k views

weighted cross entropy for imbalanced dataset - multiclass classification

I am trying to classify images to more then a 100 classes, of different sizes ranged from 300 to 4000 (mean size 1500 with std 600). I am using a pretty standard CNN where the last layer outputs a ...
5
votes
2answers
806 views

How can I have an “undefined” category in multi-class classification

I'm trying to classify several websites by category (finance, health-care, IT, etc...). I have at my disposal the content of the pages of the websites, and I use the words to classify. For now, I have ...
5
votes
4answers
8k views

How does Sigmoid activation work in multi-class classification problems

I know that for a problem with multiple classes we usually use softmax, but can we also use sigmoid? I have tried to implement digit classification with sigmoid at the output layer, it works. What I ...
5
votes
4answers
5k views

How to apply class weight to a multi-output model?

I have a model with 2 categorical outputs. The first output layer can predict 2 classes: [0, 1] and the second output layer can predict 3 classes: [0, 1, 2]. How can I apply different class weight ...
5
votes
2answers
173 views

Is K-NN applicable for binary variables?

I need help because I'm just new to machine learning and I do not know if k-nearest neighbors algorithm can be used to identify the appropriate program(s) for Student 11 in the table below. The ...
5
votes
1answer
1k views

SPARK, ML: Naive Bayes classifier often assigns 1 as probability prediction

Hi I am using Spark ML to optimise a Naive Bayes multi-class classifier. I have about 300 categories and I am classifying text documents. The training set is balanced enough and there is about 300 ...
5
votes
1answer
468 views

Multiclass classification on imbalanced dataset : Accuracy or micro F1 or macro F1

I have a multiclass classification problem. Further, an instance can be assigned to exactly one class. My dataset is highly imbalanced. I know that accuracy is not a good metric to use in this case ...
5
votes
4answers
98 views

AlexNet CNN how can it be applied to my case?

I'm working on my last year project where I'm given digitized WSI (Whole Slide Images), though they're fairly small around 1390x1040 size (which is unusual). These images are of cases of Glioblastoma ...
5
votes
2answers
56 views

Data transformations in hierarchical classification

I am building a hierarchical text classifier using the Local Classifier Per Parent Node (LCPN) approach with the 'siblings' policy as described in the A survey of hierarchical classification across ...
4
votes
2answers
3k views

Why class weight is outperforming oversampling?

I am applying both class_weight and oversampling (SMOTE) techniques on a multiclass classification problem and getting better results when using the class_weight technique. Could someone please ...
4
votes
2answers
5k views

Signs there are too many class labels

I have a classification problem, where I initially started with 100+ class labels. My intuition told me this is too many labels for a model to predict with good accuracy. I thought grouping the labels ...
4
votes
3answers
6k views

Appropriate algorithm for string (not document) classification?

I am trying to classify a large-ish number of small strings (millions) into about 10 disjunct categories. Examples of classes and strings for each class include: ...
4
votes
4answers
3k views

Scikit Learn Missing Data - Categorical values

I have a dataset containing categorical features, which has 4 labels, and 4 features. (It is a meta classifier, so outputs from base classifier serve as input into this classifier) ...
4
votes
2answers
87 views

Can I use the training rows multiple times while training with different labels attached to it?

If I have a data set where for every text message, same but two labels are given. It could be that only one label has been filled. To visualise this scenario in real life, one may classify the accent ...
4
votes
3answers
4k views

R Rpart taking too much time on data set

I am trying to build a CART model using rpart on a data set with around 7k rows and 456 columns cmodel2=rpart(DV ~ .,data=teltrain2,method="class") This has ...
4
votes
1answer
419 views

Training textblob with 16k rows of labeled data won't work (only few are working)

I've got labeled data in a csv which looks like: title,type Women Jacket A,Clothes Mens Running Shoes B,Shoes Children backpack,Bags and a script: ...
4
votes
1answer
1k views

CNN Multi-class vs Binary Class Image Classification

Suppose we have a training set of 3 classes of image: 1.Cats, 2.Dogs, 3.Neither cats nor dogs. We're only really bothered about detecting whether an image is a cat/dog, or neither, but we don't care ...
4
votes
2answers
375 views

AUC-ROC for Multi-Label Classification

Hey guys I'm currently reading about AUC-ROC and I have understood the binary case and I think that I understand the multi-classification case. Now I'm a bit confused on how to generalize it to the ...
4
votes
1answer
72 views

Difference between multinomia logistic regression and N 1 vs all binary

Is there a fundamental difference between building a set on N logistic regressions in 1 vs all fashion, as compared to training a single mutlinomial logistic regression? Put another way, are there any ...
4
votes
1answer
162 views

Why does CV yield lower score?

My training accuracy was better than my test accuracy, hence I thought my model was over-fitted and tried Cross-validation. The model further degraded. Is that my input data need to be sanitised ...
4
votes
0answers
68 views

make prediction with a time serie

I want to build a model that can detect which driver is driving now the car based on a dataset that contains 20 driver records for 3600s each driver ( the dataset contains all the car sensors values ...
4
votes
0answers
666 views

AUC computation on multilabel classification

I'm using Tensorflow for an auto-tagging task on audio clips. The problem is actually a multilabel classification problem meaning that each clip can have multiple tags at the same time. Regarding ...
3
votes
3answers
16k views

Multi-class neural net always predicting 1 class after optimization

During training, the neural net settles into a place where it always predicts 1 of the 5 classes. My train and test sets are distributed as such: ...
3
votes
3answers
1k views

Evaluation methods for multi-class classification

I am looking for single-number evaluation method that can be used in multi-class classification tasks that take into account imbalanced data-sets. For instance, ...
3
votes
2answers
461 views

True positives and true negatives, F1 score: multi class classification

I have 4 classes for an application of classification of animal kingdom: 1 --> invertibrates; 2 --> vertibrates; 3--> mammal; 4 ---> ambhibian. Given a mixture of images the objective is to identify ...
3
votes
2answers
76 views

Multiclass classification of textual data

I have a problem statement in which I have to classify the text data into various classes, but the training data is very less (250-300 data points for 4 classes). I am confused about what approach to ...
3
votes
3answers
4k views

Sklearn SVM - how to get a list of the wrong predictions?

I am not an expert user. I know that I can obtain the confusion matrix, but I would like to obtain a list of the rows that have been classified in a wrong way in order to study them after ...
3
votes
4answers
7k views

Time series feature extraction from raw sensor data for classification?

I have a tabular raw data from sensors with associated label and i want to extract the time series features like mean,max,min and std from the data all the sensor data and form another table or export ...
3
votes
2answers
462 views

How to cross-validate a deep learning model for highly imbalanced datasets?

I am working with a multi-modality classification problem (with Keras). I have 1000, 5000 and 10000 samples for three different classes. I would like to do a five ...
3
votes
2answers
6k views

Multi-class text classification with LSTM in Keras

I'm quite new to Deep Learning and trying to solve the problem of Multi-Class, multi-label text classification using Deep Learning. https://github.com/fchollet/keras/blob/master/examples/...
3
votes
2answers
2k views

How to deal with classification problem where labels are non uniformly distributed?

I have a data set which has around 1000 samples and are divided in 4 groups - A, B ,C , D. The problem I am facing is that there are very high number of data sample which have B and C s output. They ...
3
votes
1answer
129 views

Combining 'class_weight' with SMOTE

This might sound a weird question, but I could not find enough details in sklearn documentation about 'class_weight'. Can we first oversample the dataset using SMOTE and then call the classifier with ...
3
votes
1answer
170 views

Why do we Softmax at all?

Why take softmax at all at the final layer for multi-class classification problems? For example softmax of the vector [1, .5] Is [.621, .379] I mean if we just took the straight ratio, it'd give me [...

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