Questions tagged [weights]

"Weights" may refer to: (1) observation weights that come from sample surveys -- consider tagging "survey-sampling"; (2) Monte Carlo sample weights that arise when sampling from intractable distributions -- consider tagging "weighted-sampling"; (3) variable weights in statistical or machine learning models such as regression, factor analysis, or learning networks -- consider tagging with that specific model. Other odd uses of weights go here.

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Rate vs. Count Outcome with Case Weights in Random Forest

I am doing a geographic analysis to predict rate of disease in each geographic unit based on various aggregate geographic/demographic features, without any individual-level data. Each geographic unit ...
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creating index using pca

i want to create an index. it has 3 subindices A,B,C. each subindex further consists of 3 different variables A1,A2,A3,B1,B2,B3 and so on. in total there are 9 variables. i want to assign weights ...
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Question about understanding Weights of Keras LSTM model

I am implementing Federated Learning (FL) using Keras LSTM. Starting with the simple example where multiple models are trained at different clients. Each client shares their model weights with the ...
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Smoothing time series with Adjusted R2-weighted averages

I have two parameters (a,b) resulting from an exponential estimation of a curve. I have estimated this curve every hour for one month. In other words, I have a total of 720 parameters a and b, and I ...
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How to constrain ordinary kriging weights to sum to 1 in R

I need to perform ordinary kriging on a dataset and I understand that I need the weights to sum to 1, I just don't understand how to set that up properly. For example, my covariance function is C(h) =...
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Sample weighting for conditionally imbalanced classes in longitudinal cohort study

I’m conducting an analysis on a longitudinal cohort study that selected subjects with and without cognitive impairment. Subjects were recruited to maximize balance in the case and control group in ...
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Differentiating output of layer with respect to its input [duplicate]

Say we have a relationship $ z = Wx$ for a multi layer perceptron where $z$ and $x$ are $n$ dimensional vectors. When we find $\frac{dz}{dx}$ , I would assume this would just be $W$, not $W^T$. I was ...
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If the weight and bias gradients are stuck at zero throughout training, is this an indication of dying ReLu?

A high learning rate when combined with a ReLu activation function is known to lead to the 'dying ReLu' problem. Is this a reasonable conclusion to arrive at if the gradient with respect to weights ...
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Offset or weight in binomial GLM - account for distance to road on animal sightings

I am building a species distribution model for an animal, using data collected by community members when they sight this animal. My first step is to fit a generalised linear model with family binomial ...
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distribution of normalized random weights

TL;DR: Given a finite series of positive and iid random variates/weights $w_i$ of known distribution, $(w_1, ... w_n)$, what is the distribution (or at least the exp.val. and variance) of the ...
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Weighted estimation

The following equation was derived from an optimization problem. I have data on the parameters $ b, v, n $ and $ r $ and I would like to estimate the parameter $ a $ that fits the data most closely. I ...
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How to bias-correct proportions for a prop.test in R?

Let's say I ask 200 participants in a study what experience brought the most joy to their lives: A, B, C, or D. ...
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Weighted sum of Bernoulli distributions

Suppose $$ X_i \sim \text{Bernoulli }(p) $$ What can be said about the distribution of $Y$, given by $$ Y = \sum_{i=1}^N w_i X_i $$ for non-negative weights $w_i$? Note that $N$ here is small, so ...
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Independent samples z-score calculation with weighted samples

Here is some pseudo code showing how one can calculate the z-score for comparing two proportions/percentages: ...
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How to assign weights to a set of ordered objects?

I have been trying to assign weights to set of objects. The problem that I have is as following. I have a set of objects ordered either ascending or decending. . Each object shall be provided a weight ...
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Optimizing weights of elements based on their correlation to the same metric

I'm in my freshman year in college and working on a data science project the goal of which is to measure a country's prosperity. We've grouped similar indicators or elements into one pillar. We have 5 ...
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Trainable weights in attention mechanism

I am wondering what are the trainable weights inside an attention-powered transformer. I figure the feed-forward layer contain trainable weights and the token embeddings, but what other parts contain ...
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How do I calculate a finite-population correction for a weighted sample?

I have a weighted sample from a population. These are probability weights (as samples are taken with unequal probability). What's the variance in the estimated total? All samples are exchangeable (...
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Determine feature importance of nested regression model

For remote sensing purposes, I'm trying to combine data from two different satellites. To do so, one of the two has a much higher weight than the other, but this is area specific. My goal is to use a ...
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Accounting for sampling effort of independent variables in a regression analysis

I would like the test whether the frequency of a cellular structure on a histology section is associated with (binary) patient outcomes. This would be a simple logistic regression of i.e. ...
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Can I randomly eliminate survey respondents belonging to a severely over-represented group in order to allow for better weighting of data?

I have a population made of the following segments: A: 19% B: 52% C: 2% D: 10% E: 17% F: 0.5% My final sample (n=1,272), due to a much higher response rate for group C, is A: 27% B: 15% C: 38% D: 9% E:...
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Multilevel modelling weight

I want to use a nation-wide dataset which is associated with individual level weight to show the population in the US that is represented by the sample, and county-level sociodemographic census ...
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How to account for weights of a skewed dataset in a machine learning problem?

I, a novice, have a dataset which I would like to use for multiclass classification. I know that the data is skewed, but luckily, my dataset contains an observation weights column. The observation ...
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Weights for estimating ATE (rather than ATT) in SAS %CEM macro for coarsened exact matching?

I'm running Gary King's %CEM SAS macro (available here) for coarsened exact matching (CEM) for a project at work. The macro works fine for estimating the Average Treatment Effect on the Treated (ATT) ...
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Warning about factor score estimation method when using omega() from psych

I am a beginner in statistics with R. I am currently analyzing the results of a questionnaire in my PhD research. I am trying to measure reliability using McDonald's omega rather than Cronbach's alpha....
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Weighting data and causal modelling

When using causal models such as difference-in-difference or propensity score matching, will weighting the data to represent the population effect the outcome (i.e., will it bias my results)?
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How to weight examples to minimize some feature/output?

I'm working on a Regression problem consisting on predict some continuous variable $Y$, as usual. The thing here is that there are two kinds of data examples: some that have a value of $Y$ a little ...
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What if weights of model is output of neurons?

If instead of, giving axon's weights some number value, why not give it output value from other neuron. I think, taking output from neuron in previous layer and setting it as weight in current layer ...
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Are there any weight matrices of residual connections in ResNet?

In the resnet and its variants, such as (taken from here) Do these shortcut connections have any weight matrices (and bias) associated with them or do they simply copy the same output and transfer it ...
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calculating weights of questions on a questionnaire for an outcome variable

I am looking to improve the predictive validity of a questionnaire. The questionnaire to attempt to categorise the risk of someone developing a condition. There is a follow up 6 months later, and we ...
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5 votes
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Confusion about the training procedure while using transfer learning

Suppose that we have a trained CNN, there is 5 conv layers and 3 fully connected layers. We take the first 5 conv layers as it is (with their parameter settings: like kernel size, activation etc) and ...
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Should inverse probability weighting be used in two-way fixed-effects panel regression?

Let's assume a (balanced) panel data set with two measurement points $t_0$ and $t_1$, where $t_0$ may be considered as the baseline. Some of the ID's are treated at $t_1$, i.e. $D=1$, the assignment ...
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What is it even called? "Weighted rate of occurrence?" "Weighted rates"?

I know so little about this subject, that I'm not even sure what to call it. Lets say I have a giant list of machines in a factory. Some get used frequently, others not so much. I want to calculate ...
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What Lp distance should one use to calculate distance between weight vectors or vectors of regression coefficient to check convergence? [closed]

What Lp distance should one use to calculate distance between weight vectors or vectors of regression coefficient to check convergence in iterative optimization?
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Is it possible to take sample_weight in account with MLPclassifier

I am building 4 different models on the same dataset (classification tree (CT), random forest (RF), logistic regression (LR) and neural network (NN)). Here is my dataset structure: Rows correspond to ...
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Alternatives to inverse-variance weighting for aggregation?

Is there an alternative to inverse-variance weighting for aggregating the values of different estimators, that are estimating the same random variable?
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When analyzing national surveys, do I always weight the answers with the expansion factor to get represenative results?

When analyzing national surveys, do I always weigh the answers with the expansion factor to get represenative results? Alternatively, would it be wrong to just "weigh" each answer with 1 and ...
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Rank of gradient-of-loss with respect to layer weights in an MLP

The paper: https://arxiv.org/abs/2110.11309, makes the following claim at the end of page 3: The gradient of loss $L$ with respect to weights $W_l$ of an MLP is a rank-1 matrix for each of B batch ...
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Weigh the percentages based on the number of inhabitants

I am analyzing the diffusion of a service in some regions. Is there a legitimate criterion for weighing percentages by the number of inhabitants? I would like to "improve" the results of the ...
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Problem with weigts in survey analysis of GSS cross-sectional data

I have a dataset made from https://gss.norc.org/get-the-data There is a description from the codebook how to use weights: ...
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2 votes
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Find key nodes in Graph Neural Netwroks

Given a graph dataset, in which links of graphs are the same while features of each node may be varied, how can we locate those critical nodes in this graph structure that contribute the most to ...
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How to use test sample weights for prediction in XGBoost regression

I have an highly imbalanced dataset where very few y values are 'out of norm'. I want to predict as close as possible to these 'out of norm' values for those observations. For this I am trying to ...
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Building a ranking model, using linear regression with manually updated inputs by end users

I am trying to solve a ranking problem and starting from a linear regression here. As a dependent variable I currently have the score of different authors in academic literature and want to convert ...
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How do we calculate statistics on data weighted by relative frequencies?

I have the following data with some values and their corresponding weights. groups values weights a 1 0.25 a 3 0.75 b 8 1.00 The weights represent relative frequencies of each value in the group ...
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Understanding the notion of best estimators between 2 randoms variables with a weighting [duplicate]

A colleague put the mess in my head following a discussion about what he calls the "best weighting" from a statistic point of view when we treat 2 random variables. He told me that if we ...
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How to adjust sample weights in Adasboost

I am following this video tutorial to understand Adaboost I am confused about the sample weights updating. It first calculates the amount of say of each stump by this formula, where total error is ...
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Linear SVM weights interpretation in binary classification: which sign relates to which class?

I'm trying to interpret the weights of a linear svm which I use to classify elements in my dataset of patients into two classes: alzheimer and non-alzheimer. From this post I understand that the value ...
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weight variable based on opposite direction variable

I have two variables. From these two variables, I want to produce one weight variable. The first (A) is a percentage, 0.0 - 1.0. The second variable (B) is a count, 0 to infinity. I want to weight the ...
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What are some limitations of survey raking weights?

The title of this question says it all. I know that all methods have limitations, and while I know some of the strengths of raking weights (e.g., often, only marginal distributions for auxiliary ...
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Backpropagation intuitive problem

I was asked to backpropagate neural net following: where $f$ stands for sigmoid function i.e. $f(x) = \frac{1}{1 + exp(-x)}$ and $x_1 = (1, 2)$ and $y = (1, -1)$. My intuitive problem My question is ...
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