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pca related issues & queries in StatsXchanger
Autoplot disregards 'data' and 'colour'
pca
Updated April 26, 2018 05:19 AM
0
answers
4
views
0
votes
PCA for tangent space approximation
pca
Updated April 25, 2018 20:19 PM
0
answers
2
views
0
votes
PCA as preprocessing step for Linear Regression
regression
pca
Updated April 25, 2018 13:19 PM
0
answers
12
views
0
votes
pca in logistic regression
logistic
classification
pca
python
Updated April 25, 2018 08:19 AM
0
answers
4
views
0
votes
How to reduce the data into different dimensions using PCA in Matlab?
pca
matlab
dimensionality-reduction
Updated April 24, 2018 23:19 PM
0
answers
6
views
0
votes
Should I standardize or normalize variables before conducting a principal components analysis
machine-learning
pca
Updated April 24, 2018 22:19 PM
1
answers
12
views
0
votes
Help in Understanding Variational Autoencoders
machine-learning
pca
deep-learning
autoencoders
variational-bayes
Updated April 24, 2018 19:19 PM
0
answers
3
views
0
votes
Principal Component Analysis Eliminate Noise In The Data
machine-learning
neural-networks
pca
noise
Updated April 23, 2018 10:19 AM
2
answers
2337
views
4
votes
Principal component regression: some loadings are null. Is there any problem?
r
pca
Updated April 22, 2018 12:19 PM
0
answers
9
views
0
votes
What do empty (missing) values in the output of PCA or factor analysis mean in R?
r
pca
factor-analysis
Updated April 22, 2018 12:19 PM
2
answers
492
views
1
votes
Dimensionality reduction using SVD
pca
dimensionality-reduction
svd
Updated April 22, 2018 11:19 AM
0
answers
2
views
0
votes
Calculating group PCA
pca
Updated April 22, 2018 01:19 AM
0
answers
2
views
0
votes
PCA center and scale: prove the existence of a nul eigenvalues
pca
Updated April 21, 2018 23:19 PM
0
answers
4
views
0
votes
PCA regression worse than non-PCA under multicollinearity
regression
multiple-regression
pca
Updated April 21, 2018 21:19 PM
0
answers
4
views
0
votes
Discrete data & alternatives to PCA
pca
discrete-data
correspondence-analysis
mixed-type-data
Updated April 20, 2018 16:19 PM
1
answers
2790
views
8
votes
Choropleth visualisation to show variations from correlation
pca
data-visualization
metric
Updated April 20, 2018 07:19 AM
0
answers
4
views
0
votes
How exactly is sparse PCA better than PCA?
machine-learning
pca
sparse
Updated April 20, 2018 05:19 AM
3
answers
2895
views
13
votes
How does SPSS compute the component score coefficient matrix?
pca
spss
Updated April 19, 2018 14:19 PM
0
answers
4
views
0
votes
Scaled vs non-scaled PCA, which is more accurate?
pca
Updated April 17, 2018 13:19 PM
0
answers
3
views
0
votes
Does it make sense to pass HOG values to PCA and pass that result to SVM or Naive Bayes for classification?
classification
pca
svm
feature-selection
identifiability
Updated April 17, 2018 06:19 AM
0
answers
2
views
0
votes
TruncatedSVD always reduces dataset to 1D
machine-learning
pca
scikit-learn
svd
Updated April 17, 2018 00:19 AM
0
answers
4
views
0
votes
Supervised PCA with caret
regression
classification
pca
supervised-learning
caret
Updated April 16, 2018 22:19 PM
0
answers
6
views
0
votes
Normality Test before PCA
r
pca
normalization
Updated April 16, 2018 14:19 PM
0
answers
9
views
0
votes
How to assess similarity of two sets of Principal Component Analysis loadings
correlation
variance
pca
factor-analysis
factor-rotation
Updated April 16, 2018 10:19 AM
1
answers
271
views
1
votes
Creating scree plot before or after varimax rotation
r
pca
psychology
factor-rotation
Updated April 16, 2018 00:19 AM
0
answers
2
views
0
votes
Testing a low rank estimator of a covariance matrix
pca
covariance-matrix
approximation
Updated April 15, 2018 18:19 PM
0
answers
1
views
0
votes
should I use boruta feature selection on my data set and then apply PCA on the reduced features?
pca
feature-selection
Updated April 14, 2018 22:19 PM
0
answers
2
views
0
votes
Does it make sense to apply feature selection on a data set that has undergone principle component analysis?
machine-learning
pca
feature-selection
data-mining
scikit-learn
Updated April 14, 2018 18:19 PM
1
answers
4
views
0
votes
Population stratification: adjustment via principal components
pca
genetics
case-control-study
Updated April 13, 2018 12:19 PM
0
answers
3
views
0
votes
Mahalanobis distance in PCA Space
pca
distance
svd
Updated April 12, 2018 23:19 PM
0
answers
5
views
0
votes
Why is t-SNE not used as a dimensionality reduction technique for clustering?
classification
clustering
pca
dimensionality-reduction
tsne
Updated April 12, 2018 18:19 PM
0
answers
6
views
3
votes
PCA with SVD reduce dimensionality
pca
matlab
matrix
svd
Updated April 09, 2018 22:19 PM
0
answers
5
views
0
votes
PCA without response variable to get linearly dependent set of linear (mixed) model inputs
mixed-model
pca
linear-model
biostatistics
Updated April 08, 2018 17:19 PM
0
answers
4
views
0
votes
PCA on correlation or covariance?
correlation
pca
covariance
covariance-matrix
correlation-matrix
Updated April 06, 2018 20:19 PM
7
answers
83146
views
111
votes
Using Principal Component Analysis to construct a composite index
pca
Updated April 06, 2018 13:19 PM
0
answers
4
views
0
votes
pca on polar coordinates?
pca
circular-statistics
complex-numbers
Updated April 06, 2018 02:19 AM
0
answers
7
views
0
votes
Principal Component Analysis and Time Series
time-series
pca
factor-analysis
categorical-encoding
Updated April 05, 2018 15:19 PM
0
answers
12
views
1
votes
Principal Component Analysis on Time series data and panel data
time-series
pca
stata
Updated April 04, 2018 07:19 AM
1
answers
2900
views
2
votes
How do I assign meaning or give names to the latent variables in exploratory factor analysis?
pca
factor-analysis
svd
latent-variable
confirmatory-factor
Updated April 04, 2018 00:19 AM
0
answers
2
views
0
votes
PCA vs. K-means clustering - explained variance
clustering
pca
multivariate-analysis
Updated April 03, 2018 22:19 PM
1
answers
19
views
0
votes
What're the differences between PCA and autoencoder?
machine-learning
pca
neural-networks
autoencoders
Updated April 03, 2018 17:19 PM
4
answers
13572
views
33
votes
Is it possible to perform dimension reduction (e.g., PCA) on nested trial level data in R?
r
pca
Updated April 03, 2018 03:19 AM
0
answers
1
views
0
votes
If LDA (Linear Discriminant Analysis )'s basis are not orthogonal, does it make sense to re-construct the input dimension?
machine-learning
pca
factor-analysis
Updated April 02, 2018 21:19 PM
0
answers
3
views
0
votes
Is Multiple Correspondence Analysis applicable to Multi-valued Categorical Variables?
categorical-data
pca
data-mining
factor-analysis
correspondence-analysis
Updated April 02, 2018 17:19 PM
0
answers
3
views
0
votes
Percent Variance Explained - Factor Analysis
r
pca
factor-analysis
Updated April 01, 2018 16:19 PM
0
answers
10
views
0
votes
Is there a JackStraw equivalent for clustering?
clustering
pca
Updated April 01, 2018 13:19 PM
1
answers
83
views
1
votes
If the eigen values of a co-variance matrix has very low variance, what does it mean?
pca
eigenvalues
Updated March 31, 2018 17:19 PM
1
answers
10
views
0
votes
What should I check after I do PCA?
pca
factor-analysis
eigenvalues
Updated March 31, 2018 13:19 PM
0
answers
13
views
1
votes
How to Compare PCA to Non-Linear Dimensionality Reduction Techniques?
pca
dimensionality-reduction
Updated March 30, 2018 20:19 PM
0
answers
3
views
0
votes
PCA results in STATISTICA
pca
factor-analysis
Updated March 30, 2018 20:19 PM
0
answers
7
views
0
votes
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