Standardization, or normalization, is a process used to make a vector of real number values have a mean of zero and a standard deviation of one. Also called standard scores or z-scores.
Questions tagged [standardization]
72 questions
0
votes
2 answers
What is the correct syntax to standardize only some of the variables in the dataset (R)?
At first I tried:
Bank_sc <- preProcess(x = Bank,
method = c("center", "scale"),
select=c(Age, Experience, Income, Family, CCAvg, Education, Mortgage))
I have omitted one variable here, but it was…
pythonoob
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votes
1 answer
How to standardize city names inserted by user
I need to write a small ETL pipeline because I need to move some data from a source database to a target database (a datawarehouse) to perform some analysis on data.
Among those data, I need to clean and conform the name of cities. Cities are…
Simone
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votes
1 answer
Shifting from StandardScaler to MinMaxScaler causes problem
I was using StandardScaler to standardize my time series data before putting it into the RNN.
It has always worked. But now I shifted to MinMaxScaler instead. Everything works well except I cant inverse transform the data back again.
I get the…
Gustav Oskarsson
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reverse the scale of the test outcome
I am using standardized predictors in training set to train the model. When I predict the outcome in test set, how do I reverse the scale of the outcome to the original scale? It looks like I predicted the standardized score of the test…
user11806155
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1 answer
How to properly use RobustScaler for improving LinearRegression model?
As to improve my LinearRegression model I was adviced to use Standardization, i.e. RobustScaler for better performance.
My shapes of train and validation sets:
Train set: (4304, 20) (4304,)
Validation set: (1435, 20) (1435,)
So I transform my X for…
unkind58
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0
votes
1 answer
When to perform Normalization or Standardization in machine learning?
Do I have to do normalization on my data if all the features are of the same scale? for example, all the columns are features and each row/sample is the number of occurrences for each feature? And if normalization is required do I need feature-wise…
Martina Morcos
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Standardization X_train and Y_train
Im a beginner in this field and currently working on a dataset based on Facebook Ads.
The target variable is Amount spent range between 10 to 200 and the features are Frequency (range between 0.1 to 3.0) and Impressions (1000 to 30000)
After…
0
votes
1 answer
How to normalize data in R
This is my data:
a b c d e f g
14.6 74529 720 4639.341 10039.323 0.3089194 0.00011135818
270.0 74529 720 4639.341 10039.323 …
Leyla Alkan
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0
votes
1 answer
Standardizing only numerical columns
I have 2 functions to standardize my data such as:
def standartChanger(dataFrame):
stdSc = preprocessing.StandardScaler()
cols = dataFrame.columns
dfscaled = stdSc.fit_transform(dataFrame)
dfscaled = pd.DataFrame(dfscaled,…
DenizT
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votes
1 answer
Do we need to exclude OneHotEncoded columns while standardizing or normalizing using MinMaxScaler() or StandardScaler()?
This is the final cleaned DataFrame (df2) before Standardizing
my code:
scaler=StandardScaler()
df2[list(df2.columns)]=scaler.fit_transform(df2[list(df2.columns)])
df2
This returns a DataFrame after Standardizing every column including dummies and…
SAJEER AR
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-1
votes
1 answer
Is standardizing training data for a model intended to make predictions on streaming data actually realistic?
I am trying to predict activities (e.g. running, sitting, walking) based on non-streaming data with a convolutional neural network. Standardizing or normalizing the training and test data improves the predictive performance of the network…
lonyen11
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1 answer
How .scale_ is calculated by sklearn in python? (What is it's algorithm exactly?)
Please, suppose that we have an array like this:
import numpy as np
X_train = np.array([[ 1., -1., 2.],
[ 2., 0., 0.],
[ 0., 1., -1.]])
We scale it with .scale_ existed in sklearn by this code:
from…
Hamed Baziyad
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