Recent content by brojesus111

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    Optimizing Wi-Fi Network Frequencies with Graph Theory

    Yes, I see what you mean. The way I have it set up as the chromatic number will always have it be a clique of the total number of boats since every pair is adjacent to each other (thus when doing the coloring problem, it will just be the total number of boats). Is the min vertex problem just...
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    Optimizing Wi-Fi Network Frequencies with Graph Theory

    There are boats that dock in a certain port. For each pair of these boats, if they are in the port at the same time, then they will require different docks. How few docks are needed to hold all the boats? Express this problem as a graph theoretic optimization problem. The car example was...
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    Optimizing Wi-Fi Network Frequencies with Graph Theory

    I don't think all the boats are always in the port at the same time, so you're trying to optimize how few you would need. Similar to the last problem, you could have as many frequencies as there are wifi-networks, but you want to minimize it such that you only add a new one when there is a...
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    Optimizing Wi-Fi Network Frequencies with Graph Theory

    There is no restriction regarding which cars can go in which spots, just that a spot can only take one car. No groups of spots within the lot. I think a clearer question would be with boats. There are boats that dock in a certain port. For each pair of boats, if they are in the port at the...
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    Optimizing Wi-Fi Network Frequencies with Graph Theory

    Ok, I have another question if you don't mind. Problem: Say that there is a parking lot and there are n amount of cars. For each pair of cars, if they go to the same parking spot at the same time then they would need different spots. How few parking spots are required to hold all the cars...
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    Optimizing Wi-Fi Network Frequencies with Graph Theory

    Homework Statement There are n amount of wi-fi networks in a given neighborhood. For every pair that are within 50 yards, the frequency used must be different, otherwise there will be interference. How few frequencies are required so that every wi-fi network can be assigned a frequency without...
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    Optimizing Payoffs for Renting an Apartment

    Got it. I don't know why I didn't think about actually finding the values for the u_B* and u_G*. And since the boyfriend has a constant payoff in this optimization problem, the point will be Pareto efficient since the girlfriend can seek the biggest payoff without hurting the payoff of her...
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    Optimizing Payoffs for Renting an Apartment

    Homework Statement A boyfriend (B) and girlfriend (G) are going to rent an apartment. They have narrowed the offer to between $300,000 and $400,000. Their respective ordinal payoff functions for the amount spent are: u_B(x)= -2x+7 when 3 <= x <= 3.5 and 0 when 3.5 <= x <= 4 u_G(x)= 0 when 3...
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    Decision Boundary Line (Linear/Non-Linear)

    Is it because we are extending the feature space by including quadratic terms that can address this non-linearity?
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    Decision Boundary Line (Linear/Non-Linear)

    Homework Statement Given a non-linear decision boundary line: (1 + X1)^2 + (2 − X2)^2 = 4 Argue that while the decision boundary is not linear in terms of X1 and X2, it is linear in terms of X1,X1^2 , X2, and X2^2 . The Attempt at a Solution I'm honestly not sure. I realize the...
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    Experiment/Principle Components - Unsupervised Learning

    Homework Statement A researcher collects expression measurements for 1,000 genes in 100 tissue samples. The data can be written as a 1, 000 × 100 matrix, which we call X, in which each row represents a gene and each column a tissue sample. Each tissue sample was processed on a different day...
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    What Are the Limitations of KNN with High Dimensionality in LDA/QDA Performance?

    More reasons why I think my revised post above is right. The LDA's boundary is linear and it has a lower variance while the QDA's boundary is non-linear and it has a higher variance.
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    What Are the Limitations of KNN with High Dimensionality in LDA/QDA Performance?

    Actually, the only difference between LDA and QDA is that QDA assumes that each class has its own covariance matrix. So does it actually matter whether it's the test or training data? The LDA should do better when it's linear and the QDA should do better when it's non-linear. Is this correct?
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    What Are the Limitations of KNN with High Dimensionality in LDA/QDA Performance?

    Homework Statement 1. We have a set of observations on p = 100 features. The observations are uniformly distributed on each feature, and each feature ranges in value from 0 to 1. We wish to predict a test observation’s response using observations within the 10 % of each feature’s range that is...
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