Questions tagged [normalization]
Usually "normalization" means re-expressing univariate data to make values lie within a specified range.
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Normalization of absorbance data by fresh weight of samples
A [protocol] says
For each sample the absorbance (Abs) reading was divided by the fresh weight of the sample in grams. The results were normalized using an arbitrary value of 1 for the control ...
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Normalization of time-series data before computing Dynamic Time Warping (DTW)
I am interested in a proper normalization method of my time-series data before computing the dynamic time warping (DTW) distance.
Situation:
I have four time series (colored in two different green ...
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Is it wrong to use multiple normalizers sequentially on a dataset?
I am working on runoff prediction. I completed missing data and removed outliers. When it comes to normalization, applying a single normalization method (such as MinMaxScaler, StandardScaler, or Power ...
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Principal Component Analysis using Panel Data
I have a panel data with identifiers(a,b,c,....z) and different times(t=1,2,3,....100)
I have 6 different variables (A,B,C,D,E,F) for every identifier-time observation. I attempt to use those 6 ...
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Target variable standardization for lasso regression
I am working with different models for a regression task. The range of my target variable is very small:
I noticed a very bad performance of the lasso regression and elastic net model in comparison ...
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Simple example of Log-Sum-Exp trick for continuous case
I am trying to confirm my understanding of how to apply the [Log-Sum-Exp trick to recover a posterior distribution from a log-posterior distribution. I want to consider a simple example from a model I ...
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Normalization of time-series data with time-varying variance
I'm building a neural network (CNN) model for a regression problem with time-series data. Both input and output are multi-variate zero-mean timeseries data with time-varying variance. Currently, I am ...
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Standardization vs Normalization of data
In the above example I am using 3 methods for distance calculation
1.Calculating distances of actual data
2.Standardizing the data and calculating the distances
3.Using min-max scaler and then ...
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Can principal components changed by a normalization method be used to construct original data shape with SVD
I'm planning to use an algorithm called Harmony, designed for data normalization, particularly in the context of single cell data analysis. Harmony operates by taking principal components (PCs) as ...
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How can I normalize Hedges' g from two extreme conditions around the control condition?
The variables I am discussing below are not the ones I am actually using but I think that they should give a better sense of what I am trying achieve.
I am performing a meta-analysis of some chosen ...
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How to normalise outputs of neural networks with different distribution?
I have a NN model that predicts 8 different variables. I use a multi-task learning approach, where I compute the loss between predictions and targets for each of ...
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Help interpreting normalized HMM (or otherwise) results
I have run a hidden markov model with five variables on very different scales. Because of this I normalized the input data beforehand using Carets preprocessing:
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Model comparison: with raw or normalized data?
I have developed a index of drug addiction risk whose formula is Index = 1/log10(a_given_variable). The raw values of the calculated ...
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Do I need to normalize corpus frequency if I am not comparing between corpora?
Do I need to normalize my corpus frequency, given that I am not comparing corpora? For example, if I am going to compare collocations of lexicons A, B and C in a corpus with 13 million tokens, can I ...
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Normalize age frequency data for PCA
I am working on a project to forecast house ownership rates. One dataset I have consists of number of people of each age from 1-99 per geographic area code. For example, 20 people aged 1, 59 people ...
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