Questions tagged [normalization]
Usually "normalization" means re-expressing univariate data to make values lie within a specified range.
1,240 questions
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normalization in clustering
I am working on a project where I aim to cluster provinces according to their exposure to river floods. Currently, I am considering the following indicators:
Total number of flood events / total ...
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How to normalize values to a new range [duplicate]
I have a set of values with the range -22.28 to 32.65
I need to normalize them to the range 1 to 10.
The expected result of the min and max values after the normalization is -22.28 --> 1 and 32.65 -...
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Normalizing Tables for GPA Evaluation
I am working on a PowerBI report to display student data. The primary objectives are to filter based upon the academic level (undergraduate, graduate, doctorate), School in the university (Arts & ...
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How should distribution shift in docking-derived energy features be handled when ligand size changes?
I’m using docking-derived binding energy values as input features in a machine-learning model.
All of the original data was generated from molecules of similar size, but our new dataset contains much ...
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Running statistics standardization in reinforcement learning
so i'm training DDPG agent on 6 axis arm robot to move an object from A to B. The inputs are the coordinate of the joints along with the coordinate of the object that need to be moved.
So, i'm kinda ...
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Scale difference between predictions and real values?
I am comparing time series of volumes of products in different orders of magnitudes (some have volumes of ~1k, others 10k, 50k etc).
I have real values and predictions and want to compare the ...
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Should I normalize both train and valdiation sets or only the train set?
I have a question about normalization when merging training and validation sets for cross-validation.
Normally, I normalize using re-scaling (Min-Max Normalization) calculated from the training set ...
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Compare Hb values measured by two different hemoglobin meters
I have two sets of hemoglobin measurements from two different machines, each measuring different individuals. I don't have calibration information, but I do know the minimum and maximum values for ...
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XGBoost is NOT invariant to feature scaling [closed]
I am using the python library xgboost to predict a continuous variable Y from a continuous variable X and some other (class-) features. I suspect that my X has low predictive power, if any.
If I scale ...
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Expected value of the outer product of normalized, non-centered Student t vector
I was studying the expected value of the outer product of a normalized non-centered Gaussian vector and I found this very interesting and solved question and I am looking to generalize to a Student t ...
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Standardization after normalising the entire dataset
I am using SVR regression for that i have imported the dataset (which has already been normalized between 0 to 1 and it is a panel data) so while running the regression model i again undertook ...
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Normalizing datasets to make their variance comparable?
I'm working on processing a large variety of different data series, each being a list of numbers. Some of my series range from -1 to 1, some from 0.0001 to 0.0002, and some from 2 million to 3 ...
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Mitigate the effect of multiple residual connections
I recently came across a question that I couldn't answer based on my prior knowledge (note: not a homework, I already graduated):
Suppose, we use more than one residual connections in a transformer ...
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Is the arithmetic mean appropriate when feature scaling rates?
Certain machine learning algorithms perform better when the features of the dataset have been scaled. In particular, feature standardization (subtracting the mean and dividing by the standard ...
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Is normalization necessary when the predictions are made per group?
As a beginner in ml, I am watching a video on YouTube
about designing a model of song recommendations on Spotify. For each user, there to be predictions about which songs to be recommended.
One of the ...
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