Questions tagged [weighted-data]

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2
votes
1answer
59 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 ...
0
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1answer
21 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 ...
1
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1answer
32 views

Heterogeneous clustering with text data

I have a dataset which consists of multiple user ratings. Each rating looks similarly to: ...
187
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8answers
233k views

How to set class weights for imbalanced classes in Keras?

I know that there is a possibility in Keras with the class_weights parameter dictionary at fitting, but I couldn't find any example. Would somebody so kind to ...
0
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1answer
1k 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 ...
1
vote
0answers
63 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 ...
2
votes
1answer
308 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 (...
0
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1answer
94 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 ...
2
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1answer
49 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 ...
5
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2answers
424 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 : ...
5
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4answers
6k 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 ...
0
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0answers
8 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 ...
0
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1answer
19 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:...
2
votes
1answer
560 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+...
2
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1answer
72 views

Counting Number of Parameters in Neural Networks

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 ...
1
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0answers
19 views

Do I need to adjust frequencies or weights of rows so the right weight is given to each sample (data mining)?

The general problem type is as follows. I have about 2,500 rows of data. Each row contains data about an individual sample with sizes from around 10,000 to 200,000 (a known attribute / column), and ...
0
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1answer
40 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 ...
0
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0answers
55 views

why we use “class_weight='balanced” as a classifier parameter?

Please I have imbalanced data and at first, I used SMOTE to oversample it, and it gives a good result, then I see some code used sometimes class_weight='balanced" inside of the classifier ( RL, DT, ...
1
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0answers
57 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 ...
1
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1answer
22 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 ...
8
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4answers
4k 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 ...
0
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1answer
34 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 ...
0
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0answers
194 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 ...
2
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2answers
550 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 ...
7
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1answer
3k views

CNN - imbalanced classes, class weights vs data augmentation

I have a set of data 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 ...
5
votes
3answers
3k 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:...
1
vote
1answer
369 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 ...
5
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1answer
2k 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 ...
1
vote
0answers
142 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 ...
0
votes
1answer
49 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})*...
2
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1answer
8k 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 ...
12
votes
2answers
16k 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. ...
5
votes
1answer
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 ...
1
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0answers
14 views

Are we allowed to give the weight value for svm's predictors?

I have this public data that has 9 predictors in it and it's labeled with two classes. I tried linear svm on it (by computer) and the accuracy was fascinating. But, I I ran through this problem when ...
-2
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1answer
132 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 ...
27
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3answers
33k views

xgboost: give more importance to recent samples

Is there a way to add more importance to points which are more recent when analyzing data with xgboost?
0
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3answers
3k views

@RISK Vs R. Monte Carlo simulation in R?

Are there any cheaper or open source alternatives to @RISK or are there packages for R that would be able to perform the same tasks? http://www.palisade.com/risk/ @RISK (pronounced “at risk”) ...
4
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1answer
82 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 -...
0
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2answers
515 views

Calculate feature weight vector for one-hot-encoded data frame in R

I have the following data frame with one categorical and two numerical columns: V1 V2 V3 1 A 1 3 2 A 3 5 3 B 3 3 4 C 2 3 I have ...
3
votes
1answer
2k views

How can the process of hypertuning of XGBoost parameters be automated?

I'm using xgboost for training a model on a data with extreme class imbalance. After referring from here. After performing grid search and some manual settings, I ...
4
votes
1answer
687 views

Sklearn Linear Regression examples

Could someone give an example of the application of Tf-idf with sparse data (lots of zeros) in sklearn? I am not quite sure where to insert the weight of Tf-idf and how to rightly obtain the weight. ...
3
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2answers
2k views

How can give weight to feature before PCA

I wonder how can I give weight to my feature before employing PCA. I mean somehow weighted PCA. Because I know that one of the features is better than others and want to give importance to it in ...
6
votes
1answer
10k views

Machine learning technique to calculate weighted average weights?

I'm just starting to investigate machine learning concepts, so I'm sorry if this question is very naive, but I'm hoping that it will be an easy one to answer! I have a document matching algorithm ...
2
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2answers
230 views

Sort by average votes/ratings

I have a data set that's a dictionary of tuples. Each key represents an ID number and each tuple is (yesvotes, totalvotes). Example: ...
2
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2answers
140 views

Creating validation data for model comparison

I am working on building a scoring algorithm for student data, say the attributes are : name, location, age, class, school_name, skill1, skill2, skill3 based ...