Exam (elaborations)
CS434 Machine Learning and Data Mining Midterm
- Course
- Institution
CS434 Machine Learning and Data Mining Midterm
[Show more]
Seller
Follow
topgradesdr
Content preview
CS434 Machine Learning and DataMining Midterm
What occurs if our model makes no assumptions? - correct answer-No
learning occurs!
How many possible mappings exist for a binary vector of length d mapping to
a binary output? - correct answer-2^(2^(d)) possible mappings
What if we have n data points? - correct answer-Still 2^(2(^(d) - n) -- SO
many!
What assumption do we make for kNN? - correct answer-(i) Label changes
smoothly as features change in local regions; (ii) Each feature affects the
output independently
What assumption do we make for logistic regression? - correct answer-(i) The
relationship between input and output can be expressed linearly;
(ii) Label changes smoothly as features change locally;
(iii) Each feature effects output independently
What algorithms share a similar assumption? - correct answer-SVM,
perceptron, and linear regression - examples can be linearly separated or
predicted with a linear model
What is modelling error, and how do we reduce it? - correct answer-You chose
the wrong model / hypothesis space. Reduce by choosing a better model.
What is estimation error, and how do we reduce it? - correct answer-You didn't
have enough data. Reduce by adding more data (infinite data).
What is optimization error, and how do we reduce it? - correct answer-Your
model was not optimized well. Reduce by optimizing longer (infinite training
time), by substituting with a better optimization algorithm or model, or applying
more expensive optimization.
What is Bayes' error, and how do we reduce it? - correct answer-Your model
was unable to distinguish between overlapping distributions. Irreducible with a
, given dataset, UNLESS a new feature is introduced which meaningfully
discriminates between instances with the same features but different label. If
impossible, this error is called "irreducible".
What is overfitting? - correct answer-Model performs well on training, but
poorly on validation or test data.
What is underfitting? - correct answer-Model performs badly on training,
validation, and test data.
What is model selection? - correct answer-The process of finding the proper
hypothesis space (AKA the "model class") that neither underfits nor overfits.
This is challenging!
What is kNN? - correct answer-A type of model that predicts the label of an
unknown example by measuring some weighted average of the k neighbors
around it that are closest in distance (k-nearest). In the vanilla model, all
weights w_i are = 1.
What are the effects of extreme k-values in k-NN? - correct answer-At k=1,
training error is zero when Bayes error is zero. At k=n, every point is a
neighbor, leading to the majority class being predicted everywhere in the
dataset.
What would a generalization of k-NN to a regression task entail? - correct
answer-Take the weighted average of all the neighbors, and predict that value.
For 1-NN, just take the value of the closest neighbor.
For a regression k-NN, what would we predict when k=n? - correct
answer-The predicted value would equal the average value of the dataset.
What are the problems with k-NN? - correct answer-- Computationally
expensive: requires O(nd) for every test point, although proper choice of data
structure can reduce this cost.
- Massive datasets require lots of examples, but this can be reduced if we
remove "unimportant" examples lying in the "safe" region with many of the
same labels.
- The relative scale of features matters as well, because large distances
between large features matters more than small distances between small
features, so we should scale features [0,1].
The benefits of buying summaries with Stuvia:
Guaranteed quality through customer reviews
Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.
Quick and easy check-out
You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.
Focus on what matters
Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!
Frequently asked questions
What do I get when I buy this document?
You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.
Satisfaction guarantee: how does it work?
Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.
Who am I buying these notes from?
Stuvia is a marketplace, so you are not buying this document from us, but from seller topgradesdr. Stuvia facilitates payment to the seller.
Will I be stuck with a subscription?
No, you only buy these notes for $7.99. You're not tied to anything after your purchase.
Can Stuvia be trusted?
4.6 stars on Google & Trustpilot (+1000 reviews)
84866 documents were sold in the last 30 days
Founded in 2010, the go-to place to buy study notes for 14 years now