The correct approach for building a linear prediction model requires that we _________ first.

The coefficients in the linear model are determined using _____________ .

Question

The correct approach for building a linear prediction model requires that we _________ first.

The coefficients in the linear model are determined using _____________ .

BlackTom AI · Accepted Answer

The question asks about the preparatory step for building a linear prediction model and the method used to determine the coefficients.
First, consider what it means to build a predictive model responsibly: you should separate data into parts so that the model is evaluated on data it hasn’t seen during training. In practice, this involves partitioning the data into a training set (and typically a validation/test set as well). 
Next, the coefficients of a linear model are learned by fitting the model to the training data. This involves selecting parameter values that minimize a loss function (such as mean squared error) on the training examples, using the chosen algorithm (e.g., ordinary least squares, gradient descent). 
Now, regarding the idea of partitioning the data: doing so before training is essential to avoid data leakage and to obtain an unbiased assessment of model performance. Relying on the full dataset for training without keeping a separate test set would inflate performance estimates and misrepresent generalization.
Regarding the statement that coefficients are determined using training data only: this aligns with the standard practice that the fitting process uses only the training portion of the data. The test set should remain unseen during training so that evaluation reflects generalization.
Given that the provided answer option is "partition the data, training data only": this captures the crucial sequence of steps—separate data into training (and other) portions, then determine the model coefficients strictly from the training data, not from the held-out set. 
If there were other options, a typical incorrect choice might suggest using the entire dataset to determine coefficients, which would violate the principle of keeping test data unseen, or would imply deriving coefficients without first partitioning, which could lead to information leakage. However, since no additional options are shown here, focus remains on why splitting data before training and using only the training data to fit coefficients is the correct approach.

FA25-BL-BUS-K353-29897 Comprehension Check 4

The correct approach for building a linear prediction model requires that we _ first. The coefficients in the linear model are determined using _____ .

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