cerebral
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Robert-Forrest/cerebral
API Reference
cerebral
Robert-Forrest/cerebral
API Reference
API Reference
cerebral
cerebral
Models
Models
F
setup_
losses_
and_
metrics
F
build_
input_
layers
F
build_
base_
model
F
build_
feature_
branch
F
build_
model
F
save
F
load
F
compile_
and_
fit
F
fit
F
calculate_
prediction_
errors
F
calculate_
regression_
metrics
F
calculate_
classification_
metrics
F
evaluate_
model
F
get_
model_
prediction_
features
F
get_
model_
input_
features
F
predict
Loss
Loss
F
masked_
MSE
F
masked_
MAE
F
masked_
Pseudo
Huber
F
masked_
Huber
F
masked_
sparse_
categorical_
crossentropy
Metrics
Metrics
F
tpr
Per
Class
F
true
Positive
Rate
F
false
Positive
Rate
F
false
Negative
Rate
F
ppv
Per
Class
F
positive
Predictive
Value
F
f1
F
tnr
Per
Class
F
true
Negative
Rate
F
npv
Per
Class
F
negative
Predictive
Value
F
informedness
F
markedness
F
accuracy
F
balanced
Accuracy
F
positive
Likelihood
F
negative
Likelihood
F
diagnostic
Odds
F
fowlkes
Mallows
F
jaccard
F
calc_
R_
sq
F
calc_
RMSE
F
calc_
MAE
F
calc_
accuracy
F
calc_
f1
F
calc_
recall
F
calc_
precision
F
mean
Absolute
Deviation
F
root
Mean
Square
Deviation
K-
folds cross-
validation
K-
folds cross-
validation
F
kfolds_
split
F
kfolds
F
kfolds
Ensemble
Feature Permutation
Feature Permutation
F
permutation
Hyperparameter Tuning
Hyperparameter Tuning
C
Hyper
Model
C
Hyper
Model
Public members
Public members
M
__
init__
M
build
M
declare_
hyperparameters
M
fit
F
tune
Plot
Plot
F
plot_
training
F
plot_
results_
regression
F
plot_
results_
regression_
heatmap
F
plot_
results_
classification
F
plot_
multiclass_
roc
F
plot_
distributions
F
plot_
feature_
variation
F
plot_
correlation
F
plot_
feature_
permutation
Utilities
Utilities
F
ensure_
default_
values_
glass
F
load_
data
F
extract_
compositions
F
pretty
Name
F
calculate_
features
F
drop_
unwanted_
inputs
F
drop_
invalid_
compositions
F
remove_
correlated_
features
F
drop_
static_
features
F
merge_
duplicate_
compositions
F
get_
features_
from_
model
F
train_
test_
split
F
df_
to_
dataset
F
generate_
sample_
weights_
categorical
F
create_
datasets
F
filter_
masked
F
dense
None
Last update: Feb 09, 2023
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