gogol-prediction-0.0.1: Google Prediction SDK.

Copyright(c) 2015 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay <brendan.g.hay@gmail.com>
Stabilityauto-generated
Portabilitynon-portable (GHC extensions)
Safe HaskellNone
LanguageHaskell2010

Network.Google.Prediction.Types

Contents

Description

 

Synopsis

Service Configuration

predictionService :: Service Source

Default request referring to version 'v1.6' of the Prediction API. This contains the host and root path used as a starting point for constructing service requests.

OAuth Scopes

devstorageReadOnlyScope :: OAuthScope Source

View your data in Google Cloud Storage

devstorageReadWriteScope :: OAuthScope Source

Manage your data in Google Cloud Storage

predictionScope :: OAuthScope Source

Manage your data in the Google Prediction API

devstorageFullControlScope :: OAuthScope Source

Manage your data and permissions in Google Cloud Storage

Insert2ModelInfo

data Insert2ModelInfo Source

Model metadata.

See: insert2ModelInfo smart constructor.

Instances

insert2ModelInfo :: Insert2ModelInfo Source

Creates a value of Insert2ModelInfo with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

imiModelType :: Lens' Insert2ModelInfo (Maybe Text) Source

Type of predictive model (CLASSIFICATION or REGRESSION).

imiClassWeightedAccuracy :: Lens' Insert2ModelInfo (Maybe Text) Source

Estimated accuracy of model taking utility weights into account (Categorical models only).

imiClassificationAccuracy :: Lens' Insert2ModelInfo (Maybe Text) Source

A number between 0.0 and 1.0, where 1.0 is 100% accurate. This is an estimate, based on the amount and quality of the training data, of the estimated prediction accuracy. You can use this is a guide to decide whether the results are accurate enough for your needs. This estimate will be more reliable if your real input data is similar to your training data (Categorical models only).

imiMeanSquaredError :: Lens' Insert2ModelInfo (Maybe Text) Source

An estimated mean squared error. The can be used to measure the quality of the predicted model (Regression models only).

imiNumberLabels :: Lens' Insert2ModelInfo (Maybe Int64) Source

Number of class labels in the trained model (Categorical models only).

imiNumberInstances :: Lens' Insert2ModelInfo (Maybe Int64) Source

Number of valid data instances used in the trained model.

AnalyzeModelDescriptionConfusionMatrixRowTotals

data AnalyzeModelDescriptionConfusionMatrixRowTotals Source

A list of the confusion matrix row totals.

See: analyzeModelDescriptionConfusionMatrixRowTotals smart constructor.

Instances

analyzeModelDescriptionConfusionMatrixRowTotals Source

Arguments

:: HashMap Text Text

amdcmrtAddtional

-> AnalyzeModelDescriptionConfusionMatrixRowTotals 

Creates a value of AnalyzeModelDescriptionConfusionMatrixRowTotals with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

amdcmrtAddtional :: Lens' AnalyzeModelDescriptionConfusionMatrixRowTotals (HashMap Text Text) Source

Insert

data Insert Source

Instances

insert :: Insert Source

Creates a value of Insert with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

iStorageDataLocation :: Lens' Insert (Maybe Text) Source

Google storage location of the training data file.

iModelType :: Lens' Insert (Maybe Text) Source

Type of predictive model (classification or regression).

iTrainingInstances :: Lens' Insert [InsertTrainingInstancesItem] Source

Instances to train model on.

iUtility :: Lens' Insert [InsertUtilityItem] Source

A class weighting function, which allows the importance weights for class labels to be specified (Categorical models only).

iStoragePMMLModelLocation :: Lens' Insert (Maybe Text) Source

Google storage location of the pmml model file.

iSourceModel :: Lens' Insert (Maybe Text) Source

The Id of the model to be copied over.

iId :: Lens' Insert (Maybe Text) Source

The unique name for the predictive model.

iStoragePMMLLocation :: Lens' Insert (Maybe Text) Source

Google storage location of the preprocessing pmml file.

List

data List Source

Instances

list :: List Source

Creates a value of List with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

lNextPageToken :: Lens' List (Maybe Text) Source

Pagination token to fetch the next page, if one exists.

lKind :: Lens' List Text Source

What kind of resource this is.

lItems :: Lens' List [Insert2] Source

List of models.

lSelfLink :: Lens' List (Maybe Text) Source

A URL to re-request this resource.

InsertUtilityItem

data InsertUtilityItem Source

Class label (string).

See: insertUtilityItem smart constructor.

Instances

insertUtilityItem Source

Arguments

:: HashMap Text Double

iuiAddtional

-> InsertUtilityItem 

Creates a value of InsertUtilityItem with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

iuiAddtional :: Lens' InsertUtilityItem (HashMap Text Double) Source

Insert2

data Insert2 Source

Instances

insert2 :: Insert2 Source

Creates a value of Insert2 with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

insStorageDataLocation :: Lens' Insert2 (Maybe Text) Source

Google storage location of the training data file.

insModelType :: Lens' Insert2 (Maybe Text) Source

Type of predictive model (CLASSIFICATION or REGRESSION).

insKind :: Lens' Insert2 Text Source

What kind of resource this is.

insCreated :: Lens' Insert2 (Maybe UTCTime) Source

Insert time of the model (as a RFC 3339 timestamp).

insTrainingComplete :: Lens' Insert2 (Maybe UTCTime) Source

Training completion time (as a RFC 3339 timestamp).

insSelfLink :: Lens' Insert2 (Maybe Text) Source

A URL to re-request this resource.

insTrainingStatus :: Lens' Insert2 (Maybe Text) Source

The current status of the training job. This can be one of following: RUNNING; DONE; ERROR; ERROR: TRAINING JOB NOT FOUND

insStoragePMMLModelLocation :: Lens' Insert2 (Maybe Text) Source

Google storage location of the pmml model file.

insId :: Lens' Insert2 (Maybe Text) Source

The unique name for the predictive model.

insStoragePMMLLocation :: Lens' Insert2 (Maybe Text) Source

Google storage location of the preprocessing pmml file.

insModelInfo :: Lens' Insert2 (Maybe Insert2ModelInfo) Source

Model metadata.

InsertTrainingInstancesItem

data InsertTrainingInstancesItem Source

Instances

insertTrainingInstancesItem :: InsertTrainingInstancesItem Source

Creates a value of InsertTrainingInstancesItem with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

itiiCSVInstance :: Lens' InsertTrainingInstancesItem [JSONValue] Source

The input features for this instance.

itiiOutput :: Lens' InsertTrainingInstancesItem (Maybe Text) Source

The generic output value - could be regression or class label.

InputInput

data InputInput Source

Input to the model for a prediction.

See: inputInput smart constructor.

Instances

inputInput :: InputInput Source

Creates a value of InputInput with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

iiCSVInstance :: Lens' InputInput [JSONValue] Source

A list of input features, these can be strings or doubles.

AnalyzeDataDescriptionFeaturesItemCategoricalValuesItem

data AnalyzeDataDescriptionFeaturesItemCategoricalValuesItem Source

Instances

analyzeDataDescriptionFeaturesItemCategoricalValuesItem :: AnalyzeDataDescriptionFeaturesItemCategoricalValuesItem Source

Creates a value of AnalyzeDataDescriptionFeaturesItemCategoricalValuesItem with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

addficviValue :: Lens' AnalyzeDataDescriptionFeaturesItemCategoricalValuesItem (Maybe Text) Source

The category name.

addficviCount :: Lens' AnalyzeDataDescriptionFeaturesItemCategoricalValuesItem (Maybe Int64) Source

Number of times this feature had this value.

AnalyzeDataDescriptionFeaturesItemNumeric

data AnalyzeDataDescriptionFeaturesItemNumeric Source

Description of the numeric values of this feature.

See: analyzeDataDescriptionFeaturesItemNumeric smart constructor.

Instances

analyzeDataDescriptionFeaturesItemNumeric :: AnalyzeDataDescriptionFeaturesItemNumeric Source

Creates a value of AnalyzeDataDescriptionFeaturesItemNumeric with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

addfinMean :: Lens' AnalyzeDataDescriptionFeaturesItemNumeric (Maybe Text) Source

Mean of the numeric values of this feature in the data set.

addfinCount :: Lens' AnalyzeDataDescriptionFeaturesItemNumeric (Maybe Int64) Source

Number of numeric values for this feature in the data set.

addfinVariance :: Lens' AnalyzeDataDescriptionFeaturesItemNumeric (Maybe Text) Source

Variance of the numeric values of this feature in the data set.

Input

data Input Source

Instances

input :: Input Source

Creates a value of Input with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

iInput :: Lens' Input (Maybe InputInput) Source

Input to the model for a prediction.

AnalyzeDataDescriptionFeaturesItemCategorical

data AnalyzeDataDescriptionFeaturesItemCategorical Source

Description of the categorical values of this feature.

See: analyzeDataDescriptionFeaturesItemCategorical smart constructor.

Instances

analyzeDataDescriptionFeaturesItemCategorical :: AnalyzeDataDescriptionFeaturesItemCategorical Source

Creates a value of AnalyzeDataDescriptionFeaturesItemCategorical with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

addficValues :: Lens' AnalyzeDataDescriptionFeaturesItemCategorical [AnalyzeDataDescriptionFeaturesItemCategoricalValuesItem] Source

List of all the categories for this feature in the data set.

addficCount :: Lens' AnalyzeDataDescriptionFeaturesItemCategorical (Maybe Int64) Source

Number of categorical values for this feature in the data.

AnalyzeDataDescriptionOutputFeatureTextItem

data AnalyzeDataDescriptionOutputFeatureTextItem Source

Instances

analyzeDataDescriptionOutputFeatureTextItem :: AnalyzeDataDescriptionOutputFeatureTextItem Source

Creates a value of AnalyzeDataDescriptionOutputFeatureTextItem with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

addoftiValue :: Lens' AnalyzeDataDescriptionOutputFeatureTextItem (Maybe Text) Source

The output label.

addoftiCount :: Lens' AnalyzeDataDescriptionOutputFeatureTextItem (Maybe Int64) Source

Number of times the output label occurred in the data set.

OutputOutputMultiItem

data OutputOutputMultiItem Source

Instances

outputOutputMultiItem :: OutputOutputMultiItem Source

Creates a value of OutputOutputMultiItem with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

oomiScore :: Lens' OutputOutputMultiItem (Maybe Text) Source

The probability of the class label.

oomiLabel :: Lens' OutputOutputMultiItem (Maybe Text) Source

The class label.

Analyze

data Analyze Source

Instances

analyze :: Analyze Source

Creates a value of Analyze with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

aKind :: Lens' Analyze Text Source

What kind of resource this is.

aModelDescription :: Lens' Analyze (Maybe AnalyzeModelDescription) Source

Description of the model.

aSelfLink :: Lens' Analyze (Maybe Text) Source

A URL to re-request this resource.

aId :: Lens' Analyze (Maybe Text) Source

The unique name for the predictive model.

aErrors :: Lens' Analyze [AnalyzeErrorsItem] Source

List of errors with the data.

aDataDescription :: Lens' Analyze (Maybe AnalyzeDataDescription) Source

Description of the data the model was trained on.

AnalyzeModelDescriptionConfusionMatrix

data AnalyzeModelDescriptionConfusionMatrix Source

An output confusion matrix. This shows an estimate for how this model will do in predictions. This is first indexed by the true class label. For each true class label, this provides a pair {predicted_label, count}, where count is the estimated number of times the model will predict the predicted label given the true label. Will not output if more then 100 classes (Categorical models only).

See: analyzeModelDescriptionConfusionMatrix smart constructor.

Instances

analyzeModelDescriptionConfusionMatrix Source

Arguments

:: HashMap Text AnalyzeModelDescriptionConfusionMatrixAdditional

amdcmAddtional

-> AnalyzeModelDescriptionConfusionMatrix 

Creates a value of AnalyzeModelDescriptionConfusionMatrix with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

amdcmAddtional :: Lens' AnalyzeModelDescriptionConfusionMatrix (HashMap Text AnalyzeModelDescriptionConfusionMatrixAdditional) Source

Confusion matrix information for the true class label.

Output

data Output Source

Instances

output :: Output Source

Creates a value of Output with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

oOutputValue :: Lens' Output (Maybe Text) Source

The estimated regression value (Regression models only).

oKind :: Lens' Output Text Source

What kind of resource this is.

oOutputLabel :: Lens' Output (Maybe Text) Source

The most likely class label (Categorical models only).

oSelfLink :: Lens' Output (Maybe Text) Source

A URL to re-request this resource.

oId :: Lens' Output (Maybe Text) Source

The unique name for the predictive model.

oOutputMulti :: Lens' Output [OutputOutputMultiItem] Source

A list of class labels with their estimated probabilities (Categorical models only).

AnalyzeDataDescriptionOutputFeatureNumeric

data AnalyzeDataDescriptionOutputFeatureNumeric Source

Description of the output values in the data set.

See: analyzeDataDescriptionOutputFeatureNumeric smart constructor.

Instances

analyzeDataDescriptionOutputFeatureNumeric :: AnalyzeDataDescriptionOutputFeatureNumeric Source

Creates a value of AnalyzeDataDescriptionOutputFeatureNumeric with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

addofnMean :: Lens' AnalyzeDataDescriptionOutputFeatureNumeric (Maybe Text) Source

Mean of the output values in the data set.

addofnCount :: Lens' AnalyzeDataDescriptionOutputFeatureNumeric (Maybe Int64) Source

Number of numeric output values in the data set.

addofnVariance :: Lens' AnalyzeDataDescriptionOutputFeatureNumeric (Maybe Text) Source

Variance of the output values in the data set.

AnalyzeErrorsItem

data AnalyzeErrorsItem Source

Instances

analyzeErrorsItem Source

Arguments

:: HashMap Text Text

aeiAddtional

-> AnalyzeErrorsItem 

Creates a value of AnalyzeErrorsItem with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

aeiAddtional :: Lens' AnalyzeErrorsItem (HashMap Text Text) Source

Error level followed by a detailed error message.

AnalyzeDataDescription

data AnalyzeDataDescription Source

Description of the data the model was trained on.

See: analyzeDataDescription smart constructor.

Instances

analyzeDataDescription :: AnalyzeDataDescription Source

Creates a value of AnalyzeDataDescription with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

addOutputFeature :: Lens' AnalyzeDataDescription (Maybe AnalyzeDataDescriptionOutputFeature) Source

Description of the output value or label.

addFeatures :: Lens' AnalyzeDataDescription [AnalyzeDataDescriptionFeaturesItem] Source

Description of the input features in the data set.

AnalyzeModelDescription

data AnalyzeModelDescription Source

Description of the model.

See: analyzeModelDescription smart constructor.

Instances

analyzeModelDescription :: AnalyzeModelDescription Source

Creates a value of AnalyzeModelDescription with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

amdConfusionMatrixRowTotals :: Lens' AnalyzeModelDescription (Maybe AnalyzeModelDescriptionConfusionMatrixRowTotals) Source

A list of the confusion matrix row totals.

amdConfusionMatrix :: Lens' AnalyzeModelDescription (Maybe AnalyzeModelDescriptionConfusionMatrix) Source

An output confusion matrix. This shows an estimate for how this model will do in predictions. This is first indexed by the true class label. For each true class label, this provides a pair {predicted_label, count}, where count is the estimated number of times the model will predict the predicted label given the true label. Will not output if more then 100 classes (Categorical models only).

amdModelInfo :: Lens' AnalyzeModelDescription (Maybe Insert2) Source

Basic information about the model.

AnalyzeDataDescriptionFeaturesItemText

data AnalyzeDataDescriptionFeaturesItemText Source

Description of multiple-word text values of this feature.

See: analyzeDataDescriptionFeaturesItemText smart constructor.

Instances

analyzeDataDescriptionFeaturesItemText :: AnalyzeDataDescriptionFeaturesItemText Source

Creates a value of AnalyzeDataDescriptionFeaturesItemText with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

addfitCount :: Lens' AnalyzeDataDescriptionFeaturesItemText (Maybe Int64) Source

Number of multiple-word text values for this feature.

AnalyzeModelDescriptionConfusionMatrixAdditional

data AnalyzeModelDescriptionConfusionMatrixAdditional Source

Confusion matrix information for the true class label.

See: analyzeModelDescriptionConfusionMatrixAdditional smart constructor.

Instances

analyzeModelDescriptionConfusionMatrixAdditional Source

Arguments

:: HashMap Text Text

amdcmaAddtional

-> AnalyzeModelDescriptionConfusionMatrixAdditional 

Creates a value of AnalyzeModelDescriptionConfusionMatrixAdditional with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

amdcmaAddtional :: Lens' AnalyzeModelDescriptionConfusionMatrixAdditional (HashMap Text Text) Source

Average number of times an instance with correct class label modelDescription.confusionMatrix.(key) was wrongfully classified as this label.

AnalyzeDataDescriptionFeaturesItem

data AnalyzeDataDescriptionFeaturesItem Source

Instances

analyzeDataDescriptionFeaturesItem :: AnalyzeDataDescriptionFeaturesItem Source

Creates a value of AnalyzeDataDescriptionFeaturesItem with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

addfiText :: Lens' AnalyzeDataDescriptionFeaturesItem (Maybe AnalyzeDataDescriptionFeaturesItemText) Source

Description of multiple-word text values of this feature.

addfiNumeric :: Lens' AnalyzeDataDescriptionFeaturesItem (Maybe AnalyzeDataDescriptionFeaturesItemNumeric) Source

Description of the numeric values of this feature.

addfiIndex :: Lens' AnalyzeDataDescriptionFeaturesItem (Maybe Int64) Source

The feature index.

addfiCategorical :: Lens' AnalyzeDataDescriptionFeaturesItem (Maybe AnalyzeDataDescriptionFeaturesItemCategorical) Source

Description of the categorical values of this feature.

Update

data Update Source

Instances

update :: Update Source

Creates a value of Update with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

uCSVInstance :: Lens' Update [JSONValue] Source

The input features for this instance.

uOutput :: Lens' Update (Maybe Text) Source

The generic output value - could be regression or class label.

AnalyzeDataDescriptionOutputFeature

data AnalyzeDataDescriptionOutputFeature Source

Description of the output value or label.

See: analyzeDataDescriptionOutputFeature smart constructor.

Instances

analyzeDataDescriptionOutputFeature :: AnalyzeDataDescriptionOutputFeature Source

Creates a value of AnalyzeDataDescriptionOutputFeature with the minimum fields required to make a request.

Use one of the following lenses to modify other fields as desired:

addofText :: Lens' AnalyzeDataDescriptionOutputFeature [AnalyzeDataDescriptionOutputFeatureTextItem] Source

Description of the output labels in the data set.

addofNumeric :: Lens' AnalyzeDataDescriptionOutputFeature (Maybe AnalyzeDataDescriptionOutputFeatureNumeric) Source

Description of the output values in the data set.