Requires authorization
Get analysis of the model and the data the model was trained on. Try it now .
Request
HTTP request
GET https://www.googleapis.com/prediction/v1.6/projects/project/trainedmodels/id/analyze
Parameters
| Parameter name | Value | Description |
|---|---|---|
| Required parameters | ||
id
|
string
|
The unique name for the predictive model. |
project
|
string
|
The project associated with the model. |
Authorization
This request requires authorization with at least one of the following scopes ( read more about authentication and authorization ).
| Scope |
|---|
https://www.googleapis.com/auth/prediction
|
Request body
Do not supply a request body with this method.
Response
If successful, this method returns a response body with the following structure:
{
"kind": "prediction#analyze",
"id": string,
"selfLink": string,
"errors": [
{
(key): string
}
],
"dataDescription": {
"outputFeature": {
"numeric": {
"count": long,
"mean": string,
"variance": string
},
"text": [
{
"value": string,
"count": long
}
]
},
"features": [
{
"index": long,
"numeric": {
"count": long,
"mean": string,
"variance": string
},
"categorical": {
"count": long,
"values": [
{
"value": string,
"count": long
}
]
},
"text": {
"count": long
}
}
]
},
"modelDescription": {
"modelinfo": trainedmodels Resource,
"confusionMatrix": {
(key): {
(key): string
}
},
"confusionMatrixRowTotals": {
(key): string
}
}
}
| Property name | Value | Description | Notes |
|---|---|---|---|
kind
|
string
|
What kind of resource this is - "
prediction#analyze
".
|
|
id
|
string
|
The unique name for the predictive model. | |
selfLink
|
string
|
A URL to re-request this resource. | |
errors[]
|
list
|
List of errors with the data. | |
errors[].
(key)
|
string
|
Error level followed by a detailed error message. | |
dataDescription
|
object
|
Description of the data the model was trained on. | |
dataDescription.
outputFeature
|
object
|
Description of the output value or label. | |
dataDescription.outputFeature.
numeric
|
object
|
Description of the output values in the data set. | |
dataDescription.outputFeature.numeric.
count
|
long
|
Number of numeric output values in the data set. | |
dataDescription.outputFeature.numeric.
mean
|
string
|
Mean of the output values in the data set. | |
dataDescription.outputFeature.numeric.
variance
|
string
|
Variance of the output values in the data set. | |
dataDescription.outputFeature.
text[]
|
list
|
Description of the output labels in the data set. | |
dataDescription.outputFeature.text[].
value
|
string
|
The output label. | |
dataDescription.outputFeature.text[].
count
|
long
|
Number of times the output label occurred in the data set. | |
dataDescription.
features[]
|
list
|
Description of the input features in the data set. | |
dataDescription.features[].
index
|
long
|
The feature index. | |
dataDescription.features[].
numeric
|
object
|
Description of the numeric values of this feature. | |
dataDescription.features[].numeric.
count
|
long
|
Number of numeric values for this feature in the data set. | |
dataDescription.features[].numeric.
mean
|
string
|
Mean of the numeric values of this feature in the data set. | |
dataDescription.features[].numeric.
variance
|
string
|
Variance of the numeric values of this feature in the data set. | |
dataDescription.features[].
categorical
|
object
|
Description of the categorical values of this feature. | |
dataDescription.features[].categorical.
count
|
long
|
Number of categorical values for this feature in the data. | |
dataDescription.features[].categorical.
values[]
|
list
|
List of all the categories for this feature in the data set. | |
dataDescription.features[].categorical.values[].
value
|
string
|
The category name. | |
dataDescription.features[].categorical.values[].
count
|
long
|
Number of times this feature had this value. | |
dataDescription.features[].
text
|
object
|
Description of multiple-word text values of this feature. | |
dataDescription.features[].text.
count
|
long
|
Number of multiple-word text values for this feature. | |
modelDescription
|
object
|
Description of the model. | |
modelDescription.
modelinfo
|
nested object
|
Basic information about the model. | |
modelDescription.
confusionMatrix
|
object
|
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). | |
modelDescription.confusionMatrix.
(key)
|
object
|
Confusion matrix information for the true class label. | |
modelDescription.confusionMatrix.(key).
(key)
|
string
|
Average number of times an instance with correct class label modelDescription.confusionMatrix.(key) was wrongfully classified as this class label. | |
modelDescription.
confusionMatrixRowTotals
|
object
|
A list of the confusion matrix row totals. | |
modelDescription.confusionMatrixRowTotals.
(key)
|
string
|
Average number of instances with this true class label that were tested. |
Try it!
Use the APIs Explorer below to call this method on live data and see the response. Alternatively, try the standalone Explorer .