Topic 1 Question 218
A cinema company wants to build a model to predict customer visit patterns for the coming year. They have three years of customer visit data across 300 theaters; however, the data has been stored in different formats by different theaters. They must train the ML model. What should they do?
Use the last year of data so there are fewer inconsistencies for the model to handle.
Transform the data into a consistent format.
Group different format types and train a different model for each group.
Choose an ML model type that can process different formats of input data.
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B: Data Consistency: Before any effective machine learning modeling can occur, it is crucial that the data used is consistent and standardized. This means transforming all the data collected from different theaters into a uniform format. This process, often called data cleaning or preprocessing, ensures that the machine learning model has reliable and comparable input data across all samples, leading to more accurate and meaningful predictions.
👍 4Vivek0072024/10/29- 正解だと思う選択肢: B
B. Transform the data into a consistent format
Consistency in Data: To effectively train a machine learning model, the data must be in a consistent format across all sources. This allows the model to learn patterns from the entire dataset without being confused by variations in the data structure. Inconsistent formats can introduce noise and lead to poor model performance.
👍 2joshnort2025/01/14
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