Podcast #128: We chat with Kent C Dodds about why he loves React and discuss what life was like in the dark days before Git. Listen now.

Questions tagged [multiclass-classification]

Filter by
Sorted by
Tagged with
0
votes
1answer
16 views

Build a model to classify given string/text input

I need to build ML/NN model to classify/predict a given string pattern. Sample training data looks as shown in the image. Input will be the string in the column "Id Number", i need to tell to which ...
0
votes
2answers
46 views

How to handle addresses of the restaurants to feed the data-set in the ML model?

I have data from different restaurants which have also address of the restaurants now I want to predict the food delivery timing based on the given data, now the restaurant address is one of the ...
1
vote
1answer
48 views
+50

Tensorflow classification - maximize the accuracy of certain classes

I'm doing some experimentation and trying to train a forex trading model to classify based on three classes: Buy Sell No action Input rows are labeled as buy when ...
-1
votes
1answer
25 views

Softmax gives output vector whose sum is greater than 1 in Pytorch

I am a newbie to PyTorch. I was trying out the following network architecture to train a multi-class classifier. I used Softmax at the output layer and cross entropy as the loss function. However, the ...
1
vote
1answer
34 views

How to calculate accuracy, precision and recall, and F1 score for a keras sequential model?

I want to calculate accuracy, precision and recall, and F1 score for multi-class classification problem. I am using these lines of code mentioned below. ...
0
votes
0answers
5 views

Unseing label in PySpark MultilayerPerceptronClassifier

I'm trying to perform classification with a MLP in PySpark: ...
2
votes
2answers
32 views

how to access weights of individual Neurons in the output layers in MLPs?

im working on a neural network using Keras. Its an mlp(multi-layer perceptron). With 8 Neurons in the output layer. Is there a way I can access weights and biases of individual neurons of the output ...
1
vote
0answers
18 views

Multi-label classification with missing labels

I have a neural network that generates a vector that represents the class probabilities. Since it is a multilabel classification problem, I'm supposed to train the network using sigmoid + binary cross-...
0
votes
0answers
6 views

How to increase Overlapping in Real Dataset

How to increase overlapping in real data set, i.e, if we add some sample in majority class or add sample in overall data set the overlapping may increase, but the question is that how to add sample in ...
0
votes
0answers
4 views

Finding relevant pain points in feedbacks(open text)

I have employee feedback and need to find the appropriate pain points out of their feedback. Need help with the approach and analysis. I have provided a couple of examples below. Note: The feedbacks ...
0
votes
0answers
10 views

Improve the results of imbalanced multi-classification multi-lables data

I have 10k rows of multi-classification (x1..x27,y), size of dataframe is: 28*10k and its ...
1
vote
1answer
38 views

How does XGBoost use softmax as an objective function?

I'm quite used to seeing functions like log-loss, RMSE, cross entropy as objective functions and it's easy to imagine why minimizing these would give us the best model. What's difficult to imagine is ...
1
vote
0answers
13 views

Co-joining multi-peak histograms

I am analysing a bunch of data files which represent responsiveness of cells to addition of a drug. If a drug is not added, cell responds normally, if it is added, it shows abnormal patterns: , . We ...
1
vote
1answer
93 views

Sklearn classification report is not printing the micro avg score for multi class classification model

There are 6 class labels encoded as 0,1,2,3,4,5 While executing classification report score it outputs accuracy,macro avg,weighted avg .The micro average score is missing in the output . Im not ...
1
vote
2answers
75 views

class_weight on sklearn's DecisionTreeClassifier

Can class_weight='balanced' on scikit-learn's DecisionTreeClassifier be interpreted as having identical duplicate data points for the minority classes? I know that doesn't work that way, class_weight ...
1
vote
1answer
52 views

Risk score from Neural Network classifier (more than 2 categories)

I am trying to use a Neural Network to perform multiclass classification. The classes represent Insurance Risk Level. The most risky level is Level 1, the least risk corresponds to Level 10. The ...
0
votes
0answers
14 views

Scaling ML/DL classifier

I have been trying to find some guideline through google/stackoverflow for scaling a classification system. E.g. how can I scale a face recognition system if we want to add new people into the system? ...
0
votes
1answer
46 views

how to see in pandas the element of a csv table with many columns (>30) which the names of its columns is more than 10 character?

how to see in pandas the element of a csv table with many columns (>25) which the names of its columns is more than 10 character? I have 5000 rows and 32 columns and the label of some columns are more ...
0
votes
2answers
25 views

Highly Imbalanced dataset fro classes more than 200

I have a text dataset where I need to train a classifier to classify the titles into categories. The dataset shape is more than 575000. There are 256 target classes here. The problem is the dataset is ...
0
votes
0answers
35 views

Multi Class Text Classification

I am new in deep learning and I am trying to build a classification module which can classify text to one of 9 classes and then use the result of the classification to classify them to another set of ...
0
votes
0answers
9 views

How to extract electroglottograph/laryngograph using python(specially in “librosa”)?

in a certain project of mine which is related to feature extraction from speech data, I want to extract some electroglottograph/laryngograph from speech data, I have read some research papers but ...
0
votes
0answers
10 views

What are the best classifier for multiclass problem?

I have some heart sounds(.wav) for normal,murmur and artifact acquired through android by putting phone MIC directly on chest. I extracted time and frequency domain measures. Suggest me best ...
2
votes
2answers
54 views

Is it possible to have a default class in multi class classification?

In the general text classification problem, training a machine learning model to detect if a text belongs to one of N number of classes always yields a value in N. Even if the text that was passed to ...
0
votes
0answers
9 views

High accuracy in one v. all, lower accuracy in all vs. all

I am training a classifier (similar to logistic regression) on MNIST. I have 10 one -vs.-all classifiers for each number, each of which independently achieves >90% test set accuracy. However, when I ...
2
votes
2answers
37 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 ...
0
votes
1answer
89 views

Difference of sklearns accuracy_score() to the commonly accepted Accuracy metric

I am trying to evaluate the accuracy of a multiclass classification setting and I'm wondering why the sklearn implementation of the accuracy score deviates from the commenly agreed on accuracy score: $...
1
vote
2answers
53 views

Improving classifcation when some are less represented?

I have a multi-class classification problem. It performs quite well but on the least represented classes it doesn't. Indeed, here is the distribution : And here are the classification results (I took ...
0
votes
1answer
27 views

Data quality improvement as a part of preprocessing: Imputation

I have a python pandas dataframe representing a superset. The data contains a lot of nulls which I want to overwrite with real values. the superset has: both numerical and categorical data some ...
1
vote
0answers
19 views

How can I train a machine learning model with below characterstics? [closed]

Hi I have a classifier model to solve, which has close to 56k samples and 30 features which ...
0
votes
0answers
9 views

Shrink the training set during the learning process

Is there any way to change the size of the training set during the learning process? For example, let's say we have four classes (with their distribution): [A (90%), B (5%), C(2%), D(3%)]. Can we ...
0
votes
1answer
31 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 ...
0
votes
1answer
14 views

Saving LSTM hidden states while training and predicting for multi-class time series classification

I am trying to use an LSTM for multi-class classification of time series data. The training set has dimensions (390, 179), i.e. 390 objects with 179 time steps each. There are 37 possible classes. ...
1
vote
1answer
44 views

What is the purpose of 'oversampling' when the test set is still unbalanced?

I understand that both training and testing sets should have the same distribution and also understand that we should not touch the test set (in terms of oversampling). But we know that oversampling ...
0
votes
2answers
57 views

How to implement an LSTM RNN with multiple input features

EDIT: Now I didn't convert to list. I am training LSTM for multiple time-series in an array which has a structure: 450x801. There are 450 time series with each of 801 timesteps / time series. The ...
2
votes
0answers
21 views

Does object detection do a better job at image classification than image classification

I read in an article that object segmentation can do object detection better than object detection algorithms. I assume this is because there is more detailed information in the annotation images. I ...
0
votes
1answer
27 views

Feature Engineering in Multi-class Classification

I am working on a 3 class classification problem. I am curious on what is the best way to bin continuous variables for this problem. When I worked previously on 2 class problems, for examples sale ...
2
votes
0answers
37 views

Can I turn any binary classification algorithms into multiclass algorithms using softmax and cross-entropy loss?

Softmax + cross-entropy loss for multiclass classification is used in ML algorithms such as softmax regression and (last layer of) neural networks. I wonder if this method could turn any binary ...
1
vote
1answer
30 views

Are more classes more favorable than a single combined class?

Imagine the following scenario. Train a classifier that classifies an object into one of these n+m classes: ...
1
vote
0answers
22 views

How to identify multiple lines/clusters in a single dataset

I'm currently struggling to wrap my head around how multi-linear regression could be done to find separate sets of linear models in a single data set. I can perform regression on single data set for a ...
2
votes
1answer
101 views

Transform multi-label problem to multi-class problem

What are the downsides of modelling a multi-label problem as a multi-class problem with a single classifier? Let my clarify what I mean. There at least two ways that one multi-label problem can be ...
0
votes
1answer
41 views

Which feature to use in feature selection?

Objective: Multiclass classification with supervised learning, small dataset (25h) Context: My dataset is composed of mobile network data collected with a smartphone. The labels correspond to the ...
1
vote
1answer
30 views

better confussion matrix higher LogLoss ? Is that possible>

I have tried a 2 different versions of a gbm in a multinomial classification problem. The second model results in better confusion matrix but in worse Log Loss value (at the test sample). How is that ...
0
votes
1answer
172 views

RuntimeError: Assertion `cur_target >= 0 && cur_target < n_classes' failed

I am referring this previously asked question in stack-overflow which remains unsolved till now. I am facing same problem with pytorch when I am solving ...
0
votes
0answers
23 views

Can we have a sampled sigmoid instead of softmax?

Thh solution proposed here: is for softmax negative sampling. How do we do a sigmoid negative sampling? I couldnt find a corresponding 'tf.nn.sampled_sigmoid_loss' function.
0
votes
0answers
15 views

Loss function for multi-class classifiction where output variable is a level i.e the various classes are dependent on each other

Let's say we are classifying Images of cat , fish and human. Classifying a cat as human is as wrong as classifying it as fish, so here the normal loss functions/ metrics like Confusion matrix is fine. ...
0
votes
0answers
9 views

Classifying Short Texts with Spatial Features

I have a dataset of short texts (like tweets) in addition there's some geographical data attached to each tweet - coordinates, whether it was made on the road, street, outside or in the building, ...
0
votes
0answers
28 views

What DNN topology can I use to tackle a hierarchical multi-class classification problem?

Suppose that the sample set consists of labelled data, where each label corresponds to a class (say a sub-topic), and every class belongs to a group (a topic). The model should be able to predict the ...
0
votes
0answers
15 views

threshold for word/embeddings based on frequency in DNNLinearCombinedClassifier

I'm using Tensorflow's DNNLinearCombinedClassifier for multi-class classification. Irrespective of my vocabulary size I'm ...
1
vote
2answers
81 views

Difference between LASSO penalty in neural network and just LASSO regression

I wonder whether those two have any significant differences. I think in neural network, the lasso penalty put on the loss function makes the model simpler and introduces more sparsity by ...
0
votes
2answers
43 views

Keras input for multivariate classification with LSTM using current features and previous timesteps features and y values

I am working on a multivariate binary classification problem. What I want to do is to predict a binary classification given the features at the current timestep and the data (features+real ...