Q2. Given the following data:| Past Trend | Open Interest | Trading Volume | Return ||------------|---------------|----------------|--------|| Positive | Low | High | Up || Negative | High | Low | Down || Positive | Low | High | Up || Positive | High | High | Up || Negative | Low | High | Down || Positive | Low | Low | Down || Positive | Low | High | Up || Negative | High | High | Down || Negative | Low | High | Down || Positive | Low | Low | Down || Positive | High | High | Up |What is Gini Index? Using Gini Index, construct a decision tree based on the Open Interest as the target variable. List out all the intermittent steps till the tree has a height of 3.

The Gini Index is calculated by subtracting the sum of the squared probabilities of each class from…

Q2. Given the following data: Past Trend Open Interest Trading Volume Return Positive Low High Up Negative High Low Down Positive Low High Up Positive High High Up Negative Low High Down Positive Low Low Down Negative High High Down Negative Low High Down Positive Low Low Down Positive High High Up What is Gini Index. Using Gini Index, construct a decision tree based on the Open Interest as the target variable. List out all the intermittent steps till the tree has a height of 3

Q2. Given the following data: Past Trend Open Interest Trading Volume Return Positive Low High Up Negative High Low Down Positive Low High Up Positive High High Up Negative Low High Down Positive Low Low Down Negative High High Down Negative Low High Down Positive Low Low Down Positive High High Up What is Gini Index. Using Gini Index, construct a decision tree based on the Open Interest as the target variable. List out all the intermittent steps till the tree has a height of 3

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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The stand rental system is going to be used by any company to search for stands, either by prices, by prices, or by types. If there is any interest then the company will request a quotation through the system. This request will be assessed by a salesman of INSIGHTS. The salesman will issue a quotation accordingly. In the case the prices are convenient, the company will reserve the stands that it is interested in. The company has three days to pay the costs of the stands. The costs are obtained from the invoice generated by the salesman. The company can cancel its reservation any time. Furthermore, before the starting of the event, an employee of INSIGHTS with the role of supervisor will generate a report about the companies that paid the fees and the current setup of the exhibition. The supervisor will also issue the necessary reminders to the companies to bring their equipment as well as bring their promotion documents to the site of the exhibition. In order to implement the expected…
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Draw a decision tree (Full or simplified) to represent the Claremont School catalog. The Claremont School course catalog reads as follows: “A student must complete two prerequisites, CIS 110 and CIS 206, in order to enroll in CIS 288, which is an advanced course. A student who completes either one of these prerequisites and obtains the instructor’s permission, however, will be allowed to take CIS 288.”
Use decision tree to further explore the dataset, where the dependent variable is ‘smoker’. Please explain the approach taken. [No more than 300 words]
What type of algorithm would you use to segment customers into a groups? Assume the groups are npt already labeled. O Regression O Decision Trees O K-Means O Random Forest Cluster Regresssion
In a recent study on world happiness, participants were asked to evaluate their current lives on a scale from 0 to 10, where O represents the worst possible life and 10 represents the best possible life. The responses were normally distributed, with a mean of 5.3 and a standard deviation of 1.9. Answer parts (a)-(d) below. (a) Find the probability that a randomly selected study participant's response was loss than 4. The probability that a randomly selected study participant's response was lons than 4 is (Round to four decimal placos as needed.)
In order to minimize an FA, you have to try and determine if any of the states are actually the same state. You can do this by a table a table and finally by tables that shaped table All the results are stored in a nifty "stair step" that prevents any state from being compared to
At each branch, the data is partitioned into two or more categories using a decision tree. If the decision tree is not pruned, using this strategy might end up being counterproductive. When should you prune, and why?
We want to train a binary Logistic Regression classifier for the given trainingdataset:
The following dataset is a historic record of 14 houses that were sold in a small town in BC. The dataset is used to predict whether a new house in the same town will be sold in 10 days if listed with a specific price based on certain attributes. We are considering only four attributes (price, number of bedrooms, size, and distance to bus stop) just to simplify the calculations in this assignment but more attributes should be considered in real applications. Build a decision tree to predict whether a new house listing in the same town will be sold in 10 days based on the given attributes. Use ID3 algorithm. To answer this question, you need to complete the following steps: Calculate the entropy of the whole dataset After identifying the first attribute, repeat the same steps to identify the next attribute to split on in every leaf of the tree based on information gain analysis. Repeat this step until you complete the tree. Draw the final tree
3. Build the best Decision Tree for following table. Explain the process and all equations are used. Not : The solution is manual, not programming Tid Refund Marital Taxable Status Income Cheat Single 125K Married 100K Yes No 2 No No No Single 70K No 4 Yes Married 120K No No Divorced 95K Yes 6 No Married 60K No Yes Divorced 220K No Single Married 90K 8. No 85K Yes 9 No 75K No 10 No Single Yes 4. Produce rules for Table in question 3.
Let's look at the minimax search tree illustrated in Figure 2. In this diagram, black nodes represent decisions made by the MAX player, while white nodes represent decisions made by the MIN player. The squares at the terminal nodes represent payments, with the number indicating the amount paid from MIN to MAX (a 0 indicates no payment from MIN to MAX). MAX aims to maximize the payment they receive, while MIN aims to minimize the payment they make. If we apply the α-β pruning algorithm, we can analyze the minimax tree as shown in Figure 2. (a) Assume that we iterate over nodes from right to left; what are the arcs that are pruned by α-β pruning, if any? (b)Does you answer change if we iterate over nodes from left to right?