MLS-C01 Modeling Practice Question
A company is using Amazon SageMaker to deploy a model that predicts customer churn. The model was trained using a linear learner algorithm. During inference, the endpoint returns predictions that are always 0.5 (the probability of churn). What is the most likely cause?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The learning rate is set too high, causing the model to converge to the mean prediction
If the model always outputs 0.5, it suggests that the model is not learning and is stuck at the prior probability. This often happens when the learning rate is too high (causing divergence) or too low (causing slow convergence) so that the model does not update weights. The other options would cause different symptoms: data imbalance might bias towards 0 or 1, not exactly 0.5; feature scaling issues typically cause NaN or poor convergence; insufficient epochs might not converge but not necessarily give exactly 0.5.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The dataset is highly imbalanced, and the model is predicting the majority class
Why it's wrong here
Imbalance would typically cause predictions to be close to 0 or 1, not 0.5.
- ✗
The model was trained with too few epochs
Why it's wrong here
Too few epochs might lead to underfitting but predictions would vary based on the initial weights, not be constant 0.5.
- ✗
The input features are not normalized
Why it's wrong here
Unnormalized features can lead to poor convergence but not necessarily a constant 0.5.
- ✓
The learning rate is set too high, causing the model to converge to the mean prediction
Why this is correct
A high learning rate can cause the model to overshoot and settle at the mean of the target variable.
Go deeper
Related to this question
About these practice questions
This MLS-C01 question is part of Courseiva's 1,672-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.