Golang machinelearning.New函数代码示例

func ExampleMachineLearning_CreateMLModel() {
	sess, err := session.NewSession()
	if err != nil {
		fmt.Println("failed to create session,", err)
		return
	}

	svc := machinelearning.New(sess)

	params := &machinelearning.CreateMLModelInput{
		MLModelId:            aws.String("EntityId"),    // Required
		MLModelType:          aws.String("MLModelType"), // Required
		TrainingDataSourceId: aws.String("EntityId"),    // Required
		MLModelName:          aws.String("EntityName"),
		Parameters: map[string]*string{
			"Key": aws.String("StringType"), // Required
			// More values...
		},
		Recipe:    aws.String("Recipe"),
		RecipeUri: aws.String("S3Url"),
	}
	resp, err := svc.CreateMLModel(params)

	if err != nil {
		// Print the error, cast err to awserr.Error to get the Code and
		// Message from an error.
		fmt.Println(err.Error())
		return
	}

	// Pretty-print the response data.
	fmt.Println(resp)
}

func ExampleMachineLearning_UpdateMLModel() {
	svc := machinelearning.New(nil)

	params := &machinelearning.UpdateMLModelInput{
		MLModelID:      aws.String("EntityId"), // Required
		MLModelName:    aws.String("EntityName"),
		ScoreThreshold: aws.Double(1.0),
	}
	resp, err := svc.UpdateMLModel(params)

	if err != nil {
		if awsErr, ok := err.(awserr.Error); ok {
			// Generic AWS error with Code, Message, and original error (if any)
			fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr())
			if reqErr, ok := err.(awserr.RequestFailure); ok {
				// A service error occurred
				fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID())
			}
		} else {
			// This case should never be hit, the SDK should always return an
			// error which satisfies the awserr.Error interface.
			fmt.Println(err.Error())
		}
	}

	// Pretty-print the response data.
	fmt.Println(awsutil.StringValue(resp))
}

func ExampleMachineLearning_CreateBatchPrediction() {
	sess, err := session.NewSession()
	if err != nil {
		fmt.Println("failed to create session,", err)
		return
	}

	svc := machinelearning.New(sess)

	params := &machinelearning.CreateBatchPredictionInput{
		BatchPredictionDataSourceId: aws.String("EntityId"), // Required
		BatchPredictionId:           aws.String("EntityId"), // Required
		MLModelId:                   aws.String("EntityId"), // Required
		OutputUri:                   aws.String("S3Url"),    // Required
		BatchPredictionName:         aws.String("EntityName"),
	}
	resp, err := svc.CreateBatchPrediction(params)

	if err != nil {
		// Print the error, cast err to awserr.Error to get the Code and
		// Message from an error.
		fmt.Println(err.Error())
		return
	}

	// Pretty-print the response data.
	fmt.Println(resp)
}

func ExampleMachineLearning_CreateBatchPrediction() {
	svc := machinelearning.New(nil)

	params := &machinelearning.CreateBatchPredictionInput{
		BatchPredictionDataSourceID: aws.String("EntityId"), // Required
		BatchPredictionID:           aws.String("EntityId"), // Required
		MLModelID:                   aws.String("EntityId"), // Required
		OutputURI:                   aws.String("S3Url"),    // Required
		BatchPredictionName:         aws.String("EntityName"),
	}
	resp, err := svc.CreateBatchPrediction(params)

	if err != nil {
		if awsErr, ok := err.(awserr.Error); ok {
			// Generic AWS Error with Code, Message, and original error (if any)
			fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr())
			if reqErr, ok := err.(awserr.RequestFailure); ok {
				// A service error occurred
				fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID())
			}
		} else {
			// This case should never be hit, the SDK should always return an
			// error which satisfies the awserr.Error interface.
			fmt.Println(err.Error())
		}
	}

	// Pretty-print the response data.
	fmt.Println(awsutil.StringValue(resp))
}

func ExampleMachineLearning_Predict() {
	svc := machinelearning.New(nil)

	params := &machinelearning.PredictInput{
		MLModelID:       aws.String("EntityId"), // Required
		PredictEndpoint: aws.String("VipURL"),   // Required
		Record: map[string]*string{ // Required
			"Key": aws.String("VariableValue"), // Required
			// More values...
		},
	}
	resp, err := svc.Predict(params)

	if err != nil {
		if awsErr, ok := err.(awserr.Error); ok {
			// Generic AWS error with Code, Message, and original error (if any)
			fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr())
			if reqErr, ok := err.(awserr.RequestFailure); ok {
				// A service error occurred
				fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID())
			}
		} else {
			// This case should never be hit, the SDK should always return an
			// error which satisfies the awserr.Error interface.
			fmt.Println(err.Error())
		}
	}

	// Pretty-print the response data.
	fmt.Println(awsutil.StringValue(resp))
}

func ExampleMachineLearning_CreateDataSourceFromS3() {
	svc := machinelearning.New(nil)

	params := &machinelearning.CreateDataSourceFromS3Input{
		DataSourceID: aws.String("EntityId"), // Required
		DataSpec: &machinelearning.S3DataSpec{ // Required
			DataLocationS3:       aws.String("S3Url"), // Required
			DataRearrangement:    aws.String("DataRearrangement"),
			DataSchema:           aws.String("DataSchema"),
			DataSchemaLocationS3: aws.String("S3Url"),
		},
		ComputeStatistics: aws.Boolean(true),
		DataSourceName:    aws.String("EntityName"),
	}
	resp, err := svc.CreateDataSourceFromS3(params)

	if err != nil {
		if awsErr, ok := err.(awserr.Error); ok {
			// Generic AWS error with Code, Message, and original error (if any)
			fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr())
			if reqErr, ok := err.(awserr.RequestFailure); ok {
				// A service error occurred
				fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID())
			}
		} else {
			// This case should never be hit, the SDK should always return an
			// error which satisfies the awserr.Error interface.
			fmt.Println(err.Error())
		}
	}

	// Pretty-print the response data.
	fmt.Println(awsutil.StringValue(resp))
}

func ExampleMachineLearning_Predict() {
	sess, err := session.NewSession()
	if err != nil {
		fmt.Println("failed to create session,", err)
		return
	}

	svc := machinelearning.New(sess)

	params := &machinelearning.PredictInput{
		MLModelId:       aws.String("EntityId"), // Required
		PredictEndpoint: aws.String("VipURL"),   // Required
		Record: map[string]*string{ // Required
			"Key": aws.String("VariableValue"), // Required
			// More values...
		},
	}
	resp, err := svc.Predict(params)

	if err != nil {
		// Print the error, cast err to awserr.Error to get the Code and
		// Message from an error.
		fmt.Println(err.Error())
		return
	}

	// Pretty-print the response data.
	fmt.Println(resp)
}

func ExampleMachineLearning_DescribeMLModels() {
	sess, err := session.NewSession()
	if err != nil {
		fmt.Println("failed to create session,", err)
		return
	}

	svc := machinelearning.New(sess)

	params := &machinelearning.DescribeMLModelsInput{
		EQ:             aws.String("ComparatorValue"),
		FilterVariable: aws.String("MLModelFilterVariable"),
		GE:             aws.String("ComparatorValue"),
		GT:             aws.String("ComparatorValue"),
		LE:             aws.String("ComparatorValue"),
		LT:             aws.String("ComparatorValue"),
		Limit:          aws.Int64(1),
		NE:             aws.String("ComparatorValue"),
		NextToken:      aws.String("StringType"),
		Prefix:         aws.String("ComparatorValue"),
		SortOrder:      aws.String("SortOrder"),
	}
	resp, err := svc.DescribeMLModels(params)

	if err != nil {
		// Print the error, cast err to awserr.Error to get the Code and
		// Message from an error.
		fmt.Println(err.Error())
		return
	}

	// Pretty-print the response data.
	fmt.Println(resp)
}

func ExampleMachineLearning_DescribeTags() {
	sess, err := session.NewSession()
	if err != nil {
		fmt.Println("failed to create session,", err)
		return
	}

	svc := machinelearning.New(sess)

	params := &machinelearning.DescribeTagsInput{
		ResourceId:   aws.String("EntityId"),             // Required
		ResourceType: aws.String("TaggableResourceType"), // Required
	}
	resp, err := svc.DescribeTags(params)

	if err != nil {
		// Print the error, cast err to awserr.Error to get the Code and
		// Message from an error.
		fmt.Println(err.Error())
		return
	}

	// Pretty-print the response data.
	fmt.Println(resp)
}

func ExampleMachineLearning_GetMLModel() {
	sess, err := session.NewSession()
	if err != nil {
		fmt.Println("failed to create session,", err)
		return
	}

	svc := machinelearning.New(sess)

	params := &machinelearning.GetMLModelInput{
		MLModelId: aws.String("EntityId"), // Required
		Verbose:   aws.Bool(true),
	}
	resp, err := svc.GetMLModel(params)

	if err != nil {
		// Print the error, cast err to awserr.Error to get the Code and
		// Message from an error.
		fmt.Println(err.Error())
		return
	}

	// Pretty-print the response data.
	fmt.Println(resp)
}

func ExampleMachineLearning_DescribeDataSources() {
	svc := machinelearning.New(nil)

	params := &machinelearning.DescribeDataSourcesInput{
		EQ:             aws.String("ComparatorValue"),
		FilterVariable: aws.String("DataSourceFilterVariable"),
		GE:             aws.String("ComparatorValue"),
		GT:             aws.String("ComparatorValue"),
		LE:             aws.String("ComparatorValue"),
		LT:             aws.String("ComparatorValue"),
		Limit:          aws.Int64(1),
		NE:             aws.String("ComparatorValue"),
		NextToken:      aws.String("StringType"),
		Prefix:         aws.String("ComparatorValue"),
		SortOrder:      aws.String("SortOrder"),
	}
	resp, err := svc.DescribeDataSources(params)

	if err != nil {
		// Print the error, cast err to awserr.Error to get the Code and
		// Message from an error.
		fmt.Println(err.Error())
		return
	}

	// Pretty-print the response data.
	fmt.Println(resp)
}

func ExampleMachineLearning_GetEvaluation() {
	svc := machinelearning.New(nil)

	params := &machinelearning.GetEvaluationInput{
		EvaluationId: aws.String("EntityId"), // Required
	}
	resp, err := svc.GetEvaluation(params)

	if err != nil {
		if awsErr, ok := err.(awserr.Error); ok {
			// Generic AWS error with Code, Message, and original error (if any)
			fmt.Println(awsErr.Code(), awsErr.Message(), awsErr.OrigErr())
			if reqErr, ok := err.(awserr.RequestFailure); ok {
				// A service error occurred
				fmt.Println(reqErr.Code(), reqErr.Message(), reqErr.StatusCode(), reqErr.RequestID())
			}
		} else {
			// This case should never be hit, the SDK should always return an
			// error which satisfies the awserr.Error interface.
			fmt.Println(err.Error())
		}
	}

	// Pretty-print the response data.
	fmt.Println(awsutil.Prettify(resp))
}

func ExampleMachineLearning_CreateDataSourceFromS3() {
	sess, err := session.NewSession()
	if err != nil {
		fmt.Println("failed to create session,", err)
		return
	}

	svc := machinelearning.New(sess)

	params := &machinelearning.CreateDataSourceFromS3Input{
		DataSourceId: aws.String("EntityId"), // Required
		DataSpec: &machinelearning.S3DataSpec{ // Required
			DataLocationS3:       aws.String("S3Url"), // Required
			DataRearrangement:    aws.String("DataRearrangement"),
			DataSchema:           aws.String("DataSchema"),
			DataSchemaLocationS3: aws.String("S3Url"),
		},
		ComputeStatistics: aws.Bool(true),
		DataSourceName:    aws.String("EntityName"),
	}
	resp, err := svc.CreateDataSourceFromS3(params)

	if err != nil {
		// Print the error, cast err to awserr.Error to get the Code and
		// Message from an error.
		fmt.Println(err.Error())
		return
	}

	// Pretty-print the response data.
	fmt.Println(resp)
}

func ExampleMachineLearning_UpdateDataSource() {
	sess, err := session.NewSession()
	if err != nil {
		fmt.Println("failed to create session,", err)
		return
	}

	svc := machinelearning.New(sess)

	params := &machinelearning.UpdateDataSourceInput{
		DataSourceId:   aws.String("EntityId"),   // Required
		DataSourceName: aws.String("EntityName"), // Required
	}
	resp, err := svc.UpdateDataSource(params)

	if err != nil {
		// Print the error, cast err to awserr.Error to get the Code and
		// Message from an error.
		fmt.Println(err.Error())
		return
	}

	// Pretty-print the response data.
	fmt.Println(resp)
}

func ExampleMachineLearning_UpdateMLModel() {
	sess, err := session.NewSession()
	if err != nil {
		fmt.Println("failed to create session,", err)
		return
	}

	svc := machinelearning.New(sess)

	params := &machinelearning.UpdateMLModelInput{
		MLModelId:      aws.String("EntityId"), // Required
		MLModelName:    aws.String("EntityName"),
		ScoreThreshold: aws.Float64(1.0),
	}
	resp, err := svc.UpdateMLModel(params)

	if err != nil {
		// Print the error, cast err to awserr.Error to get the Code and
		// Message from an error.
		fmt.Println(err.Error())
		return
	}

	// Pretty-print the response data.
	fmt.Println(resp)
}