For small training sets variance may contribute more to the overall error than bias. Sometimes this...

For small training sets variance may contribute more to the overall error than bias. Sometimes this is handled by reducing the complexity of the model, even if the model is too simple. Why do you suppose this is the case? Come up with your own example of this

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milcah answered 1 year ago

Sketch a graph of variance, training error, typcial squared bias, Bayes error and the test error...

Sketch a graph of variance, training error, typcial squared bias, Bayes error and the test error curves on a plot. X-axis represents the flexibility and y-axis represents the value for each curve. Explain the reason of the shape of each curve.

a) Give real life examples of Bias & Variance b) For any given dataset, different sets...

a) Give real life examples of Bias & Variance b) For any given dataset, different sets of weights in SoftMax may give zero hinge loss during training. Which sets of weights would you prefer & why? Which changes would you make in SoftMax classification algorithm to enforce those preferences? c) Do you think SoftMax is better than SVM in terms of performance? Briefly explain d) Write a scenario where using SVM might be a better option than SoftMax. Hint: think...

describe what are interest groups and why sometimes small interest groups are more successful than large...

describe what are interest groups and why sometimes small interest groups are more successful than large ones.

Sometimes heritable characteristics that do not contribute to greater survival or reproduction become more common in...

Sometimes heritable characteristics that do not contribute to greater survival or reproduction become more common in a population over time, through the process of genetic drift. Define genetic drift, and explain how it can lead to changes in the frequency of certain characteristics within a population (i.e., evolution

Why is the Mean Square due to Error a better estimate of the population variance than...

Why is the Mean Square due to Error a better estimate of the population variance than the Mean Square due to Treatment? When is the Mean Square due to Treatment also a good estimate for the population variance? Why?

Discuss why an organization may decide to target more than one market segment. If more than...

Discuss why an organization may decide to target more than one market segment. If more than one segment is targeted, what challenges do you think may exist?

Sometimes more than one atom arrangement is possible, these are called geometric isomers. For the molecules...

Sometimes more than one atom arrangement is possible, these are called geometric isomers. For the molecules below sketch all the possible geometric isomers. Then keeping in mind that nonbonding pairs on the central atom will try to get as far away as possible from both other bonding and nonbonding pairs, predict which will be the prefferred geometry in nature. Justify your choice. Name the molecular geometry of the prefferred structure. SF4(2 isomers) BrF3(3 isomers) XeF4(2 isomers)

2. There may be only one or there may be more than one correct response to...

2. There may be only one or there may be more than one correct response to this question. You need only mark any one of the possible correct responses to be marked correct. A - Touch the top of the electroscope with your finger B - Remove your finger from the top of the electroscope C - Touch the top of the electroscope with a glass rod that was just previously rubbed by silk D - Touch the top of...

Which of the following statements concerning the variance are correct? (NOTE: THERE CAN BE MORE THAN...

Which of the following statements concerning the variance are correct? (NOTE: THERE CAN BE MORE THAN ONE CORRECT ANSWER) a.The larger the variance, the greater the total risk of the investment. b.If a stock portfolio is well-diversified, then the portfolio variance may be less than the variance of the least risky stock in the portfolio. c.The larger the variance, the smaller the standard deviation. d.The larger the variance, the more the actual returns tend to differ from the average return....

Some modelers prefer to partition the data into three data sets (training/validation/test) vs. the more typical...

Some modelers prefer to partition the data into three data sets (training/validation/test) vs. the more typical two data sets (training/validation). A test set can be used during the final modeling step to measure the expected prediction error in practice given that it has been totally separated from the modeling/validation process. Do you think it is important to partition the data into three data sets (training/validation/test) or just two (training/validation)? Justify your opinion by discussing the pros and cons of each...

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