pinterest oa for mle intern 2024

Imagine that you are working for a financial services company, and you are tasked with creating a model which predicts the likelihood that an individual will default on a loan (i.e., stops making the required repayments). The initial model you created has a predictive accuracy that’s only marginally better than chance, so you are considering an ensemble learning approach. Please select all appropriate options that should be considered for using ensemble learning.
Select all correct options.
a. If the dataset contains both linear and non-linear relationships, ensemble learning approaches are useful for combining them
b. Ensemble learning techniques typically creates overfitted models
c. Ensemble learning techniques can be time intensive to train
d. If the dataset contains both linear and non-linear relationships, ensemble learning approaches typically result in lower model performance compared to most approaches
e. Modern ensemble learning techniques can improve overall model interpretability

You have been dev

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游客，您好！
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r trained has to go through a validation process
b. Every algorithm used during bootstrap aggregation are inherently prone to prevent overfitting
c. Every classifier trained during bootstrap aggregation is considered a weak classifier
d. Bootstrap aggregation uses a combination of weak and strong classifiers
e. Bootstrap aggregation uses sampling with replacement
f. None of the above

Coding: Find the longest continous substring with only one character
ML coding: Backpropagation and naive bayes classifier

已加米，谢谢分享。请问backprop是implement一个简单FNN的backward pass吗

在这里通过OA的最低分数是多少？

楼主神通了，这么详尽