Surprise
v1.1.0
User Guide
Getting Started
Using prediction algorithms
How to build your own prediction algorithm
Notation standards, References
FAQ
API Reference
prediction_algorithms package
The model_selection package
similarities module
accuracy module
dataset module
Trainset class
Reader class
dump module
Surprise
Docs
»
Index
Edit on GitHub
Index
A
|
B
|
C
|
D
|
F
|
G
|
I
|
K
|
L
|
M
|
N
|
P
|
Q
|
R
|
S
|
T
|
U
|
Y
A
AlgoBase (class in surprise.prediction_algorithms.algo_base)
all_items() (surprise.Trainset method)
all_ratings() (surprise.Trainset method)
all_users() (surprise.Trainset method)
B
BaselineOnly (class in surprise.prediction_algorithms.baseline_only)
best_estimator (surprise.model_selection.search.GridSearchCV attribute)
(surprise.model_selection.search.RandomizedSearchCV attribute)
best_index (surprise.model_selection.search.GridSearchCV attribute)
(surprise.model_selection.search.RandomizedSearchCV attribute)
best_params (surprise.model_selection.search.GridSearchCV attribute)
(surprise.model_selection.search.RandomizedSearchCV attribute)
best_score (surprise.model_selection.search.GridSearchCV attribute)
(surprise.model_selection.search.RandomizedSearchCV attribute)
bi (surprise.prediction_algorithms.matrix_factorization.NMF attribute)
(surprise.prediction_algorithms.matrix_factorization.SVD attribute)
(surprise.prediction_algorithms.matrix_factorization.SVDpp attribute)
bu (surprise.prediction_algorithms.matrix_factorization.NMF attribute)
(surprise.prediction_algorithms.matrix_factorization.SVD attribute)
(surprise.prediction_algorithms.matrix_factorization.SVDpp attribute)
build_anti_testset() (surprise.Trainset method)
build_full_trainset() (surprise.dataset.DatasetAutoFolds method)
build_testset() (surprise.Trainset method)
C
CoClustering (class in surprise.prediction_algorithms.co_clustering)
compute_baselines() (surprise.prediction_algorithms.algo_base.AlgoBase method)
compute_similarities() (surprise.prediction_algorithms.algo_base.AlgoBase method)
cosine() (in module surprise.similarities)
cross_validate() (in module surprise.model_selection.validation)
cv_results (surprise.model_selection.search.GridSearchCV attribute)
(surprise.model_selection.search.RandomizedSearchCV attribute)
D
Dataset (class in surprise.dataset)
DatasetAutoFolds (class in surprise.dataset)
default_prediction() (surprise.prediction_algorithms.algo_base.AlgoBase method)
dump() (in module surprise.dump)
F
fcp() (in module surprise.accuracy)
fit() (surprise.model_selection.search.GridSearchCV method)
(surprise.model_selection.search.RandomizedSearchCV method)
(surprise.prediction_algorithms.algo_base.AlgoBase method)
G
get_neighbors() (surprise.prediction_algorithms.algo_base.AlgoBase method)
global_mean (surprise.Trainset attribute)
,
[1]
GridSearchCV (class in surprise.model_selection.search)
I
ir (surprise.Trainset attribute)
K
KFold (class in surprise.model_selection.split)
KNNBaseline (class in surprise.prediction_algorithms.knns)
KNNBasic (class in surprise.prediction_algorithms.knns)
KNNWithMeans (class in surprise.prediction_algorithms.knns)
KNNWithZScore (class in surprise.prediction_algorithms.knns)
knows_item() (surprise.Trainset method)
knows_user() (surprise.Trainset method)
L
LeaveOneOut (class in surprise.model_selection.split)
load() (in module surprise.dump)
load_builtin() (surprise.dataset.Dataset class method)
load_from_df() (surprise.dataset.Dataset class method)
load_from_file() (surprise.dataset.Dataset class method)
load_from_folds() (surprise.dataset.Dataset class method)
M
mae() (in module surprise.accuracy)
msd() (in module surprise.similarities)
mse() (in module surprise.accuracy)
N
n_items (surprise.Trainset attribute)
n_ratings (surprise.Trainset attribute)
n_users (surprise.Trainset attribute)
NMF (class in surprise.prediction_algorithms.matrix_factorization)
NormalPredictor (class in surprise.prediction_algorithms.random_pred)
P
pearson() (in module surprise.similarities)
pearson_baseline() (in module surprise.similarities)
PredefinedKFold (class in surprise.model_selection.split)
predict() (surprise.model_selection.search.GridSearchCV method)
(surprise.model_selection.search.RandomizedSearchCV method)
(surprise.prediction_algorithms.algo_base.AlgoBase method)
Prediction (class in surprise.prediction_algorithms.predictions)
PredictionImpossible
pu (surprise.prediction_algorithms.matrix_factorization.NMF attribute)
(surprise.prediction_algorithms.matrix_factorization.SVD attribute)
(surprise.prediction_algorithms.matrix_factorization.SVDpp attribute)
Q
qi (surprise.prediction_algorithms.matrix_factorization.NMF attribute)
(surprise.prediction_algorithms.matrix_factorization.SVD attribute)
(surprise.prediction_algorithms.matrix_factorization.SVDpp attribute)
R
RandomizedSearchCV (class in surprise.model_selection.search)
rating_scale (surprise.Trainset attribute)
Reader (class in surprise.reader)
RepeatedKFold (class in surprise.model_selection.split)
rmse() (in module surprise.accuracy)
S
ShuffleSplit (class in surprise.model_selection.split)
SlopeOne (class in surprise.prediction_algorithms.slope_one)
split() (surprise.model_selection.split.KFold method)
(surprise.model_selection.split.LeaveOneOut method)
(surprise.model_selection.split.PredefinedKFold method)
(surprise.model_selection.split.RepeatedKFold method)
(surprise.model_selection.split.ShuffleSplit method)
surprise.accuracy (module)
surprise.dataset (module)
surprise.dump (module)
surprise.model_selection.split (module)
surprise.prediction_algorithms (module)
surprise.prediction_algorithms.algo_base (module)
surprise.prediction_algorithms.predictions (module)
surprise.similarities (module)
SVD (class in surprise.prediction_algorithms.matrix_factorization)
SVDpp (class in surprise.prediction_algorithms.matrix_factorization)
T
test() (surprise.model_selection.search.GridSearchCV method)
(surprise.model_selection.search.RandomizedSearchCV method)
(surprise.prediction_algorithms.algo_base.AlgoBase method)
to_inner_iid() (surprise.Trainset method)
to_inner_uid() (surprise.Trainset method)
to_raw_iid() (surprise.Trainset method)
to_raw_uid() (surprise.Trainset method)
train_test_split() (in module surprise.model_selection.split)
Trainset (class in surprise)
U
ur (surprise.Trainset attribute)
Y
yj (surprise.prediction_algorithms.matrix_factorization.SVDpp attribute)
Read the Docs
v: v1.1.0
Versions
latest
stable
v1.1.0
v1.0.6
v1.0.5
v1.0.4
v1.0.3
v1.0.2
v1.0.1
v1.0.0
Downloads
On Read the Docs
Project Home
Builds
Free document hosting provided by
Read the Docs
.