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Exam DP-100 topic 2 question 110 discussion

Actual exam question from Microsoft's DP-100
Question #: 110
Topic #: 2
[All DP-100 Questions]

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You collect data from a nearby weather station. You have a pandas dataframe named weather_df that includes the following data:



The data is collected every 12 hours: noon and midnight.

You plan to use automated machine learning to create a time-series model that predicts temperature over the next seven days. For the initial round of training, you want to train a maximum of 50 different models.

You must use the Azure Machine Learning SDK v2 to run an automated machine learning experiment to train these models.

You need to configure the automated machine learning job and its settings.

How should you configure parameters of the classes that implement the job? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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Suggested Answer:
by umair_hanu at July 10, 2023, 8:29 a.m.

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miumau
Highly Voted 10 months ago
Shouldn't the forecast horizon be 14, since the data is in 12 hour intervals & we are asked to get data for the next 7 days? https://learn.microsoft.com/en-us/azure/machine-learning/reference-automated-ml-forecasting?view=azureml-api-2#forecasting "The maximum forecast horizon in units of time-series frequency. These units are based on the inferred time interval of your training data, (Ex: monthly, weekly) that the forecaster uses to predict."
upvoted 13 times
[Removed]
9 months, 1 week ago
My thoughts exactly
upvoted 1 times
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umair_hanu
Highly Voted 11 months, 1 week ago
IT SHOULD BE FORECASTING
upvoted 9 times
damaldon
11 months, 1 week ago
Agree, forecasting
upvoted 1 times
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a2c6d4a
Most Recent 1 week ago
the correct configuration for the parameters of the classes that implement the job is as follows: Job type: Forecasting target column name: Temperature time column name: Observation time forecast horizon: 7 days iterations: 50
upvoted 1 times
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TA_
2 months, 2 weeks ago
On exam 15-03-2024
upvoted 1 times
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NullVoider_0
4 months, 1 week ago
Forcast Horizon is 14 since the data collected is every 12 hours which is twice a day for 7 days.
upvoted 1 times
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NullVoider_0
4 months, 1 week ago
Format Horizon is 14 since the data collected is every 12 hours which is twice a day for 7 days.
upvoted 1 times
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PradhanManva
8 months, 3 weeks ago
CHATGPT - # Define your time-series forecasting task type (e.g., forecasting_future, forecasting_horizon). # Specify the column you want to predict (e.g., 'temperature') and the target lags (e.g., [1, 2, 3]). # This is important for time-series forecasting. task = 'forecasting_future' target_column_name = 'temperature' ///********** # Configure AutoML settings automl_config = AutoMLConfig( task=task, primary_metric='normalized_root_mean_squared_error', training_data=weather_df, label_column_name=target_column_name, max_models=50, # Maximum number of models to train time_column_name='timestamp', # Name of the time column in your DataFrame forecast_horizon=7 ) ********/
upvoted 1 times
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orionduo
9 months, 2 weeks ago
A regression model provides a function that describes the relationship between one or more independent variables and a response, dependent, or target variable. For example, the relationship between height and weight may be described by a linear regression model. The first anwser should be forecasting
upvoted 3 times
orionduo
9 months, 2 weeks ago
my mistake regression model can be used as prediction as well
upvoted 1 times
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PI_Team
10 months, 3 weeks ago
Task is forecasting
upvoted 1 times
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