Questions tagged [normalization]

The tag has no usage guidance, but it has a tag wiki.

Filter by
Sorted by
Tagged with
77
votes
1answer
70k views

When to use (He or Glorot) normal initialization over uniform init? And what are its effects with Batch Normalization?

I knew that Residual Network (ResNet) made He normal initialization popular. In ResNet, He normal initialization is used , while the first layer uses He uniform initialization. I've looked through ...
34
votes
1answer
12k views

Paper: What's the difference between Layer Normalization, Recurrent Batch Normalization (2016), and Batch Normalized RNN (2015)?

So, recently there's a Layer Normalization paper. There's also an implementation of it on Keras. But I remember there are papers titled Recurrent Batch Normalization (Cooijmans, 2016) and Batch ...
26
votes
1answer
21k views

Ways to deal with longitude/latitude feature [closed]

I am working on a fictional dataset with 25 features. Two of the features are latitude and longitude of a place and others are pH values, elevation, windSpeed etc with varying ranges. I can perform ...
22
votes
3answers
17k views

Data normalization before or after train-test split?

Which one is the right approach to make data normalization - before or after train-test split? Normalization before split ...
15
votes
4answers
40k views

How to scale an array of signed integers to range from 0 to 1?

I'm using Brain to train a neural network on a feature set that includes both positive and negative values. But Brain requires input values between 0 and 1. What's the best way to normalize my data?
15
votes
2answers
10k views

Is it necessary to normalise data for XGBoost?

MinMaxScaler in scikit_learn is used for data normalization (a.k.a feature scaling). Data normalisation is not necessary for decision trees. Since XGBoost is based on decision trees, is it necessary ...
15
votes
3answers
23k views

When to use Standard Scaler and when Normalizer?

I understand what Standard Scalar does and what Normalizer does, per the scikit documentation: Normalizer, Standard Scaler. I know when Standard Scaler is applied. But in which scenario is Normalizer ...
13
votes
2answers
30k views

How to normalize data for Neural Network and Decision Forest

I have a data set with 20000 samples, each has 12 different features. Each sample is either in category 0 or 1. I want to train a neural network and a decision forest to categorize the samples so that ...
13
votes
3answers
19k views

Zero Mean and Unit Variance

I'm studying Data Scaling, and in particular the Standardization method. I've understood the math behind it, but it's not clear to me why it's important to give the features zero mean and unit ...
10
votes
2answers
18k views

Would you recommend feature normalization when using boosting trees?

For some machine learning methods it is recommended to use feature normalization to use features that are on the same scale, especially for distance based methods like k-means or when using ...
9
votes
2answers
4k views

Which comes first? Multiple Imputation, Splitting into train/test, or Standardization/Normalization

I am working on a multi-class classification problem, with ~65 features and ~150K instances. 30% of features are categorical and the rest are numerical (continuous). I understand that standardization ...
9
votes
4answers
15k views

How do we standardize arrays with NaN?

I used StandardScaler() to standardize data so far, but this doesn't work with NaNs. None of the other methods I know of (MinMaxScaler, RobustScaler, MaxAbsScaler) work with NaNs either. Are there ...
9
votes
1answer
14k views

Why should I normalize also the output data?

I'm new to data science and Neural Networks in general. Looking around many people say it is better to normalize the data between doing anything with the NN. I understand how normalizing the input ...
8
votes
3answers
3k views

What is normalization for?

I am new in python and data science (and not great in math). I am learning machine learning. I got following normalize function. Can you please explain what does this normalize function do? ...
7
votes
5answers
227 views

Reducing the effect of down voters with rating system

I have a site in which users rate things in a 1-5 star system. Once an item reaches the top of the charts, some users tend to start rating it 1 star even though it got a majority of 4-5 stars to get ...
7
votes
1answer
336 views

What are some situations when normalizing input data to zero mean, unit variance is not appropriate or not beneficial?

I have seen normalization of input data to zero mean, unit variance many times in machine learning. Is this a good practice to be done all the time or are there times when it is not appropriate or not ...
7
votes
2answers
4k views

Fill missing values AND normalise

I have two columns of training data for a neural net which are missing values. (There are many other columns which aren't missing values.) For example ...
6
votes
4answers
6k views

Should input images be normalized to -1 to 1 or 0 to 1

Many ML tutorials are normalizing input images to value of -1 to 1 before feeding them to ML model. The ML model is most likely a few conv 2d layers followed by a fully connected layers. Assuming ...
6
votes
1answer
5k views

Is it valuable to normalize/rescale labels in neural network regression?

Have there been any papers, or does anyone have any specific experience to know whether normalizing labels in a regression problem is likely to improve the performance of a neural network? I have ...
6
votes
1answer
6k views

It is helpful to normalize target variables for a regression neural network?

It is customary to normalize feature variables and this normally does increase the performance of a neural network in particular a CNN. I was wondering if normalizing the target could also help ...
5
votes
3answers
2k views

How to normalize data without knowing the min and max values?

I have a Lending club dataset from Kaggle; it contains many different columns: there are for example dummy variables, years, amount of the loan...ect I want to normalize the data in the training and ...
5
votes
1answer
1k views

Financial Time Series data normalization

I'm using Keras in R to predict financial time series. It's easy to normalize price, simply compute returns or log returns, usually it's enough. I want to use Goldman Sachs Financial Conditions Index ...
5
votes
1answer
1k views

Should boolean features be normalized and should false be -1 or 0

I am attempting to train an SVM from a set of features which are both numeric and categorical, for example: Distance X (Numeric) Distance Y (Numeric) Font Size Difference (Numeric) Word 1 Bold (...
4
votes
3answers
531 views

Why models performs better If normalize test data and train data separately?

Many threads (and courses) such as this and this one suggest that you should apply normalization to the test data using the parameters used in the training set. But other some discussions I've found ...
4
votes
3answers
179 views

Understanding data normalisation

So I know that when we have different parameters with different value ranges we have to standardise these values. Also, I read that when a parameter does in fact require higher values then we should ...
4
votes
2answers
6k views

Convert exponential to normal distribution

For the distribution shown below, I want to convert the exponential distribution to a normal distribution. I want to do this is as part of data pre-processing so that the classifier can better ...
4
votes
1answer
376 views

feature scaling xgbRegressor

I read for example in this answer: Does the performance of GBM methods profit from feature scaling? that scaling doesn´t affect the performance of any tree-based method, not for lightgbm,xgboost,...
4
votes
1answer
206 views

Does the choice of normalization change dramatically the result of a KMeans

I'm using a KMeans to get the profile of several users according to several columns (I'm working with RStudio). To analyze my clusters, I decided to realize a radar chart, so I decided to use feature ...
4
votes
1answer
80 views

Should one normalize the frequency values when feeding it as an input to machine learning model?

Consider an unsupervised data. The data is in the form of a csv file( I am using pandas dataframe for this). Its a web page data at different time steps and the way I am converting data to be fed to ...
4
votes
2answers
149 views

Normalising data with multiple methods

When training a neural network, I appreciate that data normalisation helps training. However, is it a good idea to normalise the data in multiple ways. For instance, is it a good idea to apply z-score ...
4
votes
2answers
5k views

normalizing data and avoiding dividing by zero

I have data that I'm compressing with AutoEncoders (3-layer neural network) and I would like to normalize my data first. I would like to try to use the coded latent vector and feed it into an anomaly ...
3
votes
1answer
3k views

Data scaling before PCA: how to deal with categorical values?

I have to apply PCA on a dataset, which contains both numerical and categorical values. In the preprocessing phase, I converted all the categorical values in numerical, so that the software can deal ...
3
votes
1answer
3k views

Difference between normalization and zero centering

I am working on some pre-processing for lung CT images. I see a nice tutorial in here. Two of them are normalization and zero centering. I wonder what is the difference between these two steps? If one ...
3
votes
2answers
812 views

How to normalize data from multiple sources?

I am trying to model an individuals' purchasing behavior using different data sources (ex: Zalando, Otto, etc.,). When I combine data sources, I see that the data across these channels is very ...
3
votes
1answer
992 views

Why does test data need to be normalized on train data mean and std?

I understand why it is usefull to normalize data in general (at least I think I do). You take the mean and the standard deviation of the train data and apply it to both, the train and test data. Why ...
3
votes
1answer
493 views

Normalizing test data

I have a problem in data normalization. I have data for which I need to create an SVM. I will be using the model for real-time predictions. I know that the test tuples should be normalized using the ...
3
votes
1answer
207 views

How to fix inconsistent (variable spelling) categorical data and “fill in” missing data

I am a newbie data science engr. My first challenge is to (1) normalize inconsistent values in categorical features and (2) fill any missing information. To describe inconsistency lets say we have a ...
3
votes
2answers
145 views

Layer normalization details in GPT-2

I've read that GPT-2 and other transformers use layer normalization before the self-attention and feedforward blocks, but I am still unsure exactly how the normalization works. Let's say that our ...
3
votes
1answer
1k views

What is the difference between BatchNorm and Adaptive BatchNorm (AdaBN)?

I understand that BatchNorm (Batch Normalization) centers to (mean, std) = (0, 1) and potentially scales (with $ \gamma $) and offsets (with $ \beta $) the data which is input to the layer. BatchNorm ...
3
votes
1answer
6k views

Neural Network outputing the same value / normalization

I had a simple neural network that was outputting the same value regardless of the input. During training, it was behaving normally, with training and validation loss diminishing to a floor value. ...
3
votes
1answer
50 views

What parameters to use when normalising training, validation, and testing data?

I know a similar post was made here, but I wanted to ask some follow up questions. I am conducting a cross-validation search to find values of a set of hyper-parameters and need to normalise the data. ...
3
votes
0answers
36 views

A Deep CNN model delivering better results with standardization, when compared with normalization

I developed a deep CNN model, based on the architecture discussed in this paper, to generate predictions for time series data. My training data is shown in the figure below: In order to train the ...
3
votes
0answers
52 views

Standardizing data from different distributions

I have energy data from different homes (~200), and I wish to merge all the energy data to create a combined dataset. Since the individual homes have different power consumption, I get different ...
3
votes
1answer
210 views

Data normalization in nonstationary data classification with Learn++.NSE based on MLP

I need to predict technical aggregate condition using vibration monitoring data. We consider this data to be nonstationary i.e. distribution parameters and descriptive statistics are not constant. I ...
2
votes
3answers
2k views

How can I augment my image data?

What are the correct and common ways to normalize image for CNN? I used to work with text and it was pretty straightforward. Removing stop words, clean text from noise, tokenization, stemming etc. ...
2
votes
1answer
148 views

is there a way to normalize [-3,1] to ${\begin{bmatrix} \dfrac{-3}{\sqrt{10}}\\ \dfrac{1}{\sqrt{10}}\\ \end{bmatrix}}$ with python?

I am learning SVD by following this MIT course The lecturer is trying to normalize a vector $${\begin{bmatrix} -3\\ 1\\ \end{bmatrix}}$$ to $${\begin{bmatrix} \dfrac{-3}{\sqrt{10}}\\ \dfrac{1}{\...
2
votes
2answers
3k views

Why not use Scaler.fit_transform on total dataframe?

In sklearn I'm normalizing the data with MinMaxScaler. The example I'm following uses ...
2
votes
2answers
120 views

Should normalization be applied?

I have more then 100 columns with the values of 1-0. But the two features at the end as seen in the below image, have different values then the rest. Should I rescale the values in the last two ...
2
votes
1answer
153 views

Tensor Flow Time Series Tutorial Question

In the tutorial, they normalize the data and say "The mean and standard deviation should only be computed using the training data" What does this refer to? Why should you only use the training data?
2
votes
2answers
5k views

Should we denormalize our data after normalization?

If we use sklearn library's preprocessing.normalize() function to normalize our data before learning, like this: ...

1
2 3 4 5