実際的-ハイパスレートのDY0-001問題トレーリング試験-試験の準備方法DY0-001資格認定試験学ぶことは遅すぎることはありません。あなたは引き続き勉強したい場合、DY0-001認定試験資格証明書を取得する機会があります。そのほかに、多くの人がDY0-001認定試験に合格しました後、成功し、幸せになりました。給料が高い仕事を見つけたからです。あなたは決してこの有難い機会をあきらめないで、早くDY0-001学習材料を買いましょう！ CompTIA DataAI Certification Exam 認定 DY0-001 試験問題 (Q76-Q81):質問 # 76
Which of the following distance metrics for KNN is best described as a straight line?
A. Euclidean
B. Radial
C. Manhattan
D. Cosine
正解：A
解説：
Euclidean distance measures the straight-line distance between two points in space, matching the geometric "as-the-crow-flies" notion of distance.
質問 # 77
The term "greedy algorithms" refers to machine-learning algorithms that:
A. examine every node of a tree before making a decision.
B. apply a theoretical model to the distribution of the data.
C. update priors as more data is seen.
D. make the locally optimal decision.
正解：D
解説：
# Greedy algorithms make decisions based on what appears to be the best (most optimal) choice at that current moment - i.e., a locally optimal decision - without regard to whether this choice will yield the globally optimal solution.
Examples in machine learning:
* Decision Tree algorithms (e.g., CART) use greedy approaches by selecting the best split at each node based on information gain or Gini index.
Why the other options are incorrect:
* A: This refers to Bayesian updating, not greedy behavior.
* B: That describes exhaustive search, not greediness.
* C: That aligns more with probabilistic or generative models, not greedy strategies.
Official References:
* CompTIA DataX (DY0-001) Official Study Guide - Section 4.2 (Model Selection Methods):"Greedy algorithms make locally optimal decisions at each step. Decision trees, for instance, use greedy splitting based on current best criteria."
* Elements of Statistical Learning, Chapter 9:"Greedy methods make stepwise decisions that maximize immediate gains - they are fast, but may miss the global optimum."
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質問 # 78
Under perfect conditions, E. coli bacteria would cover the entire earth in a matter of days. Which of the following types of models is the best for explaining this type of growth?
A. Linear
B. Exponential
C. Logarithmic
D. Polynomial
正解：B
解説：
# Bacterial growth under ideal conditions follows exponential behavior: the population doubles at regular intervals. This results in a rapid increase that aligns with the formula: N(t) = N#e
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