Questions tagged [weighted-data]

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Weights assignment criteria for Cross-Entropy Loss

I would like to know how I could estimate the weights to apply at Cross-Entropy loss, for the multiclass semantic segmentation task, with highly imbalanced classes. ...
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10 views

Assigning weights based on outcome probability

In a classification problem, is it suitable to assign sample weights based on their positive class probability? For example, if I am building a binary classification problem where one of the ...
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27 views

Custom layers in Keras -- custom weights

I am trying to understand how to build custom layers in Keras and I went through a couple examples: here and here. The syntax is, of course, similar, but in non of the cases it is addressed why ...
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XGBoost: How to obtain scale_pos_weight for multi classes?

I know there is a similar Qn at Unbalanced multiclass data with XGBoost. But I don't understand the reply provided by @Esmailian. What is the actual formula to obtain 1, 0.333 and 0.167? ...
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Ensemble/combining models weighted by number of observations?

Across a few different projects, I have hit a problem where I have two (or more) models: General-Purpose Model: A model which is based on a large amount of data not specifically relevant to my ...
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Logistic Regression : shouldn't weighting by the number of instances give the same result ? What could explain the discrepency?

I am performing a logistic regression in a standard supervised framework (Data Set X, target y). The dataset X is composed of a handfull of categorical variables (that I one-hot encode), thus it ...
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Is there R functions that allow to test for overdispersion when fitting a model with survey design?

I realized I need to use the package survey to be able to include sample weights in my regression analysis. Initially, I wanted to use a negative binomial regression on each one of my outcomes as ...
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31 views

Weighting the loss function based on previous seen true positive rates

Similiar to class imbalance there is always something I would call "learnability imbalance" in multi-class classification. What I mean by that: Even when the classes are evenly distributed ...
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Reducing (Variance) | the gap between my weights

I have ML ready samples. And each sample has a weight. The weights distribute between [0-1] My problem arise because there are a lot of samples which are ...
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3 votes
1 answer
1k views

Specifying class or sample weights in Keras for one-hot encoded labels in a TF Dataset

I am trying to train an image classifier on an unbalanced training set. In order to cope with the class imbalance, I want either to weight the classes or the individual samples. Weighting the classes ...
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2 answers
54 views

Do we have any method which handles the imbalanced classification with sample weighting instead of class weighting?

I am looking for methods that use sample weighting instead of class weighting for the imbalanced classification. I think sample weighting is more precise than weighting all the samples from one class ...
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1 answer
198 views

Weighted accuracy, sensitivity and specificity

I have a confusion matrix TN= 27 FP=20 FN =11 TP=6 I want to calculate the weighted average for accuracy, sensitivity and specificity. I know the equation but unsure how to do the weighted averages.
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1 answer
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Integer encoding and weighing when one feature consists of more names [closed]

Hello I am trying to make a content based movie recommendation system and one feature is genre of the movie. I will give an integer number to each genre randomly. However, some movies are of more than ...
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3 answers
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Understanding Weighted learning in Ensemble Classifiers

I'm currently studying Boosting techniques in Machine Learning and I happened to understand that in Algorithms like Adaboost, each of the training samples is given a weight depending on whether it was ...
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0 answers
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Class weights in RSNSS package?

New to ML in general and have been Googling on this. I am working on a dataset that will rate each customer features to a credit worthiness class attribute. Is it possible to add class weights in the '...
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1 answer
34 views

Methods of disaggregating data to smaller units?

I have a relatively straightforward question that I know poses some difficult challenges. Let's say I have a state-level rate of X. I would like to disaggregate the state-level rate to the county-...
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1 answer
823 views

How to interpret the sample_weight parameter in MiniBatchKMeans?

I am using scikit-learn MiniBatchKMeans to do text clustering. In the fit() function there is a parameter sample_weight described as follows: The weights for each ...
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72 views

How to balance dataset using fit_generator() in Keras?

I am trying to use keras to fit a CNN model to classify 2 classes of data . I have imbalanced dataset I want to balance my data equally. How I can do that ?? Any help would be appreciated The main ...
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1 vote
1 answer
361 views

How and where to set weights in case of imbalanced cost sensitive learning in machine learning?

I confront with a binary classification machine learning task which is both slightly imbalanced and cost sensitive. I wonder what (and where in the modeling pipeline, say, in sklearn) is the best way ...
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2 answers
123 views

Assign more importance to recent records during training

My goal is to build a classification model in order to predict if a customer will buy a product or not (binary classification). Since in the last months (let's say 3-4) I know that the advertising of ...
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4 votes
1 answer
2k views

Weighted loss functions vs weighted sampling?

For image classification tasks, is there a practical difference between using weighted loss functions vs. using weighted sampling? (I would appreciate theoretical arguments, experience or published ...
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1 vote
0 answers
29 views

Non-monotone missing data, and inverse probability weighting

I'm having difficulty identifying whether or not my missing data pattern is 'monotone'. I have two variables with missing data, and the missing data patterns in each variable do not completely ...
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1 answer
132 views

When exactly should I use weighted loss?

Do I have to use it in any case when the class distribution is imbalance (Train: class A:10%, B:90% and Test: class A:10%, B:90%) or when it is different (Train: class A:10%, B:90% and Test: class A:...
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1 vote
1 answer
108 views

Heterogeneous clustering with text data

I have a dataset which consists of multiple user ratings. Each rating looks similarly to: ...
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1 answer
45 views

Closed form of Weighted Ordinary Least Squares calculation of the trend line

I would like to know if there is a closed form version of this equation: $\beta = \frac{n\sum{xy}-\sum{x}\sum{y}}{n\sum{x^2}-(\sum{x})^2}$ But for weighted data, where the weight $w_i$ is the value ...
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1 vote
0 answers
186 views

Grouping by 2 Columns in R to Sum, Count, Percentage, Weighted mean, mode [closed]

I am trying to use dplyr or data.table to calculate sums, percentages, counts, and weighted means for various sub groups. Each Name can have subgroups High Medium and low, and potentially others, and ...
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1 vote
1 answer
419 views

Counting Number of Parameters in Neural Networks [closed]

Note: This is an academics based problem. So in a recent in-class quiz, we were asked that if we have an input layer consisting of 20 nodes along with 2 hidden layers (one of size 10 and the other of ...
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1 vote
1 answer
38 views

On assiging weights for unbalanced classes

Consider a dataset that will be split into train and test. The model will be learned using the train set and evaluated using the unseen test set. Now the dataset is unbalanced -- it contains more ...
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2 votes
0 answers
741 views

XGBoost predicting everything as null when sample weights are passed

I am trying to build an Uplift model using observational data. The data is consists of collections calls to customers and my objective is to predict the incremental probability due to the treatment (...
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0 votes
1 answer
395 views

How to generate 12 independent random weights which all add up to one

I'm using Palisade's @Risk software with a triangular distribution to generate 12 random weights which must add up to one, but I get a lot of negative numbers. Is there a straightforward way to set ...
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0 answers
378 views

How to visualize the weights of the output(classification) layer?

I'm doing a Convolutional Neural Network of MNIST data set, and how can I visualize the weights of the output(classification) layer? I only found several websites visualizing the filters in CNN model ...
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0 votes
1 answer
182 views

Clustering with custom criterion (minimum cluster weight)

Edit: following comment from @anony-mousse, I'm changing the question to search for a general clustering approach that matches this criterion (minimum weight per cluster). I am to use a clustering ...
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2 votes
1 answer
87 views

Training a model where each response in the observation data has a different known varience

I have a dataset where each response variable is the number of successes of N Bernoulli trials with N and p (the probability of success) being different for each observation. The goal is to train a ...
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9 votes
1 answer
7k views

CNN - imbalanced classes, class weights vs data augmentation

I have a dataset with a few strongly imbalanced classes, eg. the smallest class is about 54 times smaller than the largest. Therefore, data augmentation in order to equalize the size of classes seems ...
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  • 155
1 vote
1 answer
951 views

How are weights calculated in a feed-forward neural network before they are summed up with bias?

I have read a lot of papers and watched different videos, it seems like they explain how they are summed up with bias before entering the activation function. What I am trying to understand is the ...
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11 votes
1 answer
5k views

Why doesn't class weight resolve the imbalanced classification problem?

I know that in imbalanced classification, the classifier tends to predict all the test labels as larger class label, but if we use class weight in loss function, it would be reasonable to expect the ...
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2 votes
1 answer
883 views

Calculate weighted mean for two columns and hundreds of rows?

I'm trying to teach myself basics of R and I couldn't find the answer: Say, I have a csv file and I want to calculate weighted mean for each subject such that I have a mean mu = 0.015*1030+0.16*26930+...
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10 votes
6 answers
17k 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 ...
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6 votes
3 answers
4k views

using sklearn class weight to increase number of positive guesses in extremely unbalanced data set?

Hi I have a poorly correlated and unbalanced data set I have to work with. The set is 2 classes, 0 has 96,000 values and 1 has about 200. When I run random forest or other methods I get an output like:...
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1 vote
1 answer
511 views

How to weight loss in regression

I've got a regression problem where a model is required to predict a value in the range [0, 1]. I've tried to look at the distribution of the data and and it seems that there are more examples with ...
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0 votes
1 answer
2k views

Class weights for imbalanced data in multilabel problems

I am trying to train a CNN for a multiclass - multilabel classification task (20 classes, each sample can belong to 1+ labels) and the dataset is highly imbalanced. In single-label cases I would use ...
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5 votes
2 answers
1k views

How to use class_weight parameter for validation set?

I am using Keras' class_weight parameter to deal with an imbalanced class problem. I am doing this to define the weights : ...
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0 votes
1 answer
86 views

Differentiating roadmap of a loss function

Let's say I'm performing Stochastic Gradient Descent (SGD) on binary cross entropy error while optimizing weight $w_{2}$. Binary cross entropy error: $$L(y|p(x_{i}))=-y_{i}*ln(p(x_{i}))-(1-y_{i})*...
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2 votes
1 answer
12k views

How to set class-weight for imbalanced classes in KerasClassifier while it is used inside the GridSearchCV?

Could you please let me know how to set class-weight for imbalanced classes in KerasClassifier while it is used inside the ...
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18 votes
2 answers
29k views

Sample Importance (Training Weights) in Keras

How do you add more importance to some samples than others (sample weights) in Keras? I'm not looking for class_weightwhich is a fix for unbalanced datasets. ...
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2 votes
2 answers
870 views

emphasise some observation weights more than the others

I want to emphasise (increase the weight) of only a subset of data. Lets say I have old and fresh data, I would like to say that old data has to have more weight and therefore has more influence in ...
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5 votes
1 answer
2k views

Purpose of weights in neural networks

I'm beginner at Neural Networks. After reading multiple articles on wikipedia, i've seen the term "weight" being used a lot, although it is a little confusing. I know, that before the inputs are ...
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-2 votes
1 answer
288 views

How to redistribute weightage proportionally?

I want to increase proportional increase weightage. For example, I have weights w1 = 0.4 w2 = 0.3 w3 = 0.2 w4 = 0.1 with a constraint that the total sum of the ...
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  • 101
4 votes
1 answer
84 views

Range to define emotions

We are capturing emotions as survey responses. We need to assign values for the responses(emotions) for analysis purposes. Is there an optimum range that can be assigned to achieve this? (like from -...
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8 votes
4 answers
6k views

Unbalanced class: class_weight for ML algorithms in Spark MLLib

In python sklearn, there are multiple algorithms (e.g. regression, random forest ... etc.) that have the class_weight parameter to handle unbalanced data. However, I do not find such parameter for ...
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