Using KNN method, predict the most likely performance for a new part-time staff with personality grade 3 and motivation grade 3. Use Euclidean distance to measure the distance in your answer. Determine your answer using K=1 and K=3. Compare and comment on your answer.

Using KNN method, predict the most likely performance for a new part-time staff with personality grade 3 and motivation grade 3. Use Euclidean distance to measure the distance in your answer. Determine your answer using K=1 and K=3. Compare and comment on your answer.

Similar questions

Why is RMSE generally the preferred performance measure for regression tasks? A. Because it gives an idea of the average percentage deviation of the predictions from the actual values. B. Because it gives an idea of the average absolute deviation of the predictions from the actual values. C. Because it gives an idea of how much error the system typically makes in its predictions, with a higher weight given to large errors. D. Because it gives an idea of the average deviation of the predictions from the actual values.
TESTING YOUR UNDERSTANDING Exercise 3-1. Consider the scenario described at the beginning of this chapter: When parents call to say that children are sick, we have to let their classroom teachers know, and if it's sports day and the child is on a school team, the sports teacher might have to sort out substitutes. Then we need to count up all the days missed to put on the child's report. The Department of Education needs the totals each term, too. Run through the steps in the summary section and sketch some use cases and an initial data model. Assume that the main objectives are to record the absences for the classroom teacher, for school reports, and for statistics given to the Department of Education.
this data sceince questions please explain in details In a survey of 1000 people, the following preference is observed. Is buying computer correlated with the student status? Is this relationship significant with 90% significance level? With a support of 30% and confidence of 30%, write two significant association rules from this dataset. Find out the maximum itemsets from this dataset considering the support threshold of 30%.
Suppose, as manager of a chain of stores, you would like to use sales transactional data to analyze the effectiveness of your store's advertisements: In particular, you would like to study how specific factors influence the effectiveness of advertisements that announce a particular category of items on sale. The factors to study are: the region in which customers live, and the day-of-the-week, and time-of-the-day of the ads. Discuss how to design an efficient method to mine the transaction data sets and explain how multidimensional and multilevel mining methods can help you derive a good solution.
The Frequentist approach looks at Question 17 options: the long-term relative frequency of events occurring both single events occurring and the long-term relative frequency of events occurring a single event occurring neither single events occurring nor the long-term relative frequency of events occurring For data that is approximately normally distributed, any observation more than 1 standard deviation away from the mean is an outlier. Question 26 options: True False
You are building a classification model to predict whether a firm will go bankrupt within the next 5 years. When you collect the data, you find that the number of instances of firms that went bankrupt is smaller than the number of cases of firms that did not go bankrupt. Specifically, only 7% of the firms went bankrupt, while the rest did not go bankrupt. Once you build the classification model, you need to compare performance against a baseline. Which of the following would be an appropriate baseline? O Always predicting that the firm does not go bankrupt O Making a prediction that a firm goes bankrupt with 7% probability O Always predicting that the firm goes bankrupt Making a prediction from the set (bankrupt, not bankrupt) with equal probability
Credit Scoring
None
The predictive performance of a model is the measure of how close the model’s prediction values are to the actual values. A close-to-ideal model would have the minimum error in the predicted and actual values. The validation set is used to assess the predictive ability of the model which has been trained using the training set. True False
Three classifiers are to be benchmarked. To this end, using the same data, the classifiers were trained and the following table shows the validation results obtained with n = 16 observations. 1 1 0 2 0 3 1 4 1 5 1 6 1 7 0 8 9 10 11 12 13 14 15 16 OTTOTOO 0 1 1 1 1 0 ZOOOoooo Hooo o Ytrue Y1 Y2 Y3 1 0 0 0 1 0 1 0 1 1 0 0 1 1 0 1 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 1 0 1 0 0 0 1 1 0 11O 1 1 1 1 0001 Match the classifiers with the performance measures. Accuracy and Error rate for Y3 Choose... Accuracy and Error rate for Y2 Choose... TPR and FPR for Y1 Choose...
You are developing a simulation model of a service system and are trying to create an input model of the customer arrival Process, You have the following four observations of the process of interest [86, 24,9, 50] and you are considering either an exponential distributionor a uniform distribution for the model. Using the data to estimate any necessary distribution Parameters, write the steps to plot Q-Q plots for both uniform and exponential distribution. Write the steps clearly. Thanks.
Assume an attribute (feature) has a normal distribution in a dataset. Assume the standard deviation is S and the mean is M. Typically: Group of answer choices, multiple choice: Then the outliers usually lie below -3*M or above +3*M Then the outliers usually lie above -3*S or below +3*S Then the outliers usually lie below -3*S or above +3*S Then the outliers usually lie above -3*M or below +3*M