PomaPLS | R Documentation |
PomaPLS
performs Partial Least Squares (PLS) regression, Partial Least Squares Discriminant Analysis (PLS-DA) to classify samples, and Sparse Partial Least Squares Discriminant Analysis (sPLS-DA) to classify samples (supervised analysis) and select variables.
PomaPLS(
data,
method = "pls",
y = NULL,
ncomp = 5,
labels = FALSE,
ellipse = TRUE,
cross_validation = FALSE,
validation = "Mfold",
folds = 5,
nrepeat = 10,
vip = 1,
num_features = 10,
theme_params = list()
)
data |
A |
method |
Character. PLS method. Options include "pls", "plsda", and "splsda". |
y |
Character. Indicates the name of |
ncomp |
Numeric. Number of components in the model. Default is 5. |
labels |
Logical. Indicates if sample names should be displayed. |
ellipse |
Logical. Indicates whether a 95 percent confidence interval ellipse should be displayed. Default is TRUE. |
cross_validation |
Logical. Indicates if cross-validation should be performed for PLS-DA ("plsda") and sPLS-DA ("splsda") methods. Default is FALSE. |
validation |
Character. (Only for "plsda" and "splsda" methods). Indicates the cross-validation method. Options are "Mfold" and "loo" (Leave-One-Out). |
folds |
Numeric. (Only for "plsda" and "splsda" methods). Number of folds for "Mfold" cross-validation method (default is 5). If the validation method is "loo", this value is set to 1. |
nrepeat |
Numeric. (Only for "plsda" and "splsda" methods). Number of times the cross-validation process is repeated. |
vip |
Numeric. (Only for "plsda" method). Indicates the variable importance in the projection (VIP) cutoff. |
num_features |
Numeric. (Only for "splsda" method). Number of features to discriminate groups. |
theme_params |
List. Indicates |
A list
with results including plots and tables.
Pol Castellano-Escuder
data("st000284")
# PLS
st000284 %>%
PomaNorm() %>%
PomaPLS(method = "pls")
data("st000336")
# PLSDA
st000336 %>%
PomaImpute() %>%
PomaNorm() %>%
PomaPLS(method = "plsda")
# PLSDA with Cross-Validation
st000336 %>%
PomaImpute() %>%
PomaNorm() %>%
PomaPLS(method = "plsda", cross_validation = TRUE)
# sPLSDA
st000336 %>%
PomaImpute() %>%
PomaNorm() %>%
PomaPLS(method = "splsda")
# sPLSDA with Cross-Validation
st000336 %>%
PomaImpute() %>%
PomaNorm() %>%
PomaPLS(method = "splsda", ncomp = 3, cross_validation = TRUE)
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