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- Create a knowledge base using frames for the description of the domain given below. Arepresentation must contain at least one class frame and all types of relations available inframes. Roland Greenberg was born in Germany in 1973. He is a sociologist by his education and has 15scientific publications. Roland collects stamps. His collection consists of 36,000 stamps from 1910to 1960. The follwoing information is known about each stamp: year of issue, title, country,monetary value and special marks (if any). One of the stamps is a stamp issued in Germany in1942 "Make the planet free!". It costs 50,000 EUR, because the stamp of the German post is seton it. Another stamp is the "Classic Fashion" released in France in 1956. It costs 3000 EUR. Could you please solve problem given above? Thankscan you make ER Diagram with Crow`s foot method about library system. The rule: 1. A member can borrow more than one book at a time 2. A member can have more than one phone number 3. A book can have more than one author 4. All book registration, member and borrowing processes can only be done/served by officers 5. Data for books, members and officers are stored with a unique id, so no id is the same.Consider the problem of trying to predict the acceptance status of an academic paper submitted to a given conference. We would like to use specific features to predict the acceptance status of a paper into one of the following categories [Accept, Weak Accept, Weak Reject, Reject, No Judgement]. We’ve decided to use a one-vs-one multi-class classification strategy: we train one classifier for each pair of classes. Later, we’re trying to predict the acceptance status of a new paper represented by sample xtest; we pass the sample into each of the models to obtain the value of hθ(xtest) for each model. The table below (on the top of the next page) summarizes the pair of classes recognized by each of the 10 models, as well as the predicted value hθ(xtest) obtained by each model on the input xtest: in this question is to use the information provided to determine which of the five classes xtest belongs to. Show your working clearly e.g. show how you compute the probability of each class and…
- Suppose you want to build a classifier for initial screening of patients who are suspected of having cancer. Patients classified as positive for cancer will be sent for further more accurate testing. The confusion matrices for classifiers A and B are given below. Which classifier is more appropriate to use to classify patients? Select one: a. Classifier A b. Classifier B c. Both are equally good and why?For the final project, you address some questions that interest you with the statistical methodology we learn in statistics 201( Elementery statics 13th e) . you choose the question; you decide how to collect data; you do the analyses. The questions can address almost any topic, including topics in psycholgy, sociology, antural science, medicine, public policy, sports, law, etc, The final project requires you to synthesize all the material from the course. Hence, it's one of the best ways to solidify your understanding of statistical methods.For the confusion matrix shown, what is the precision for classes A. B, and C? What is the recall for classes A, B, and C? What is the overall accuracy of the system? Normalized Confustion Matrix Classifier Output (Computed Classification) Prediction A B C True Class of the Samples (Input) A 0.81 0.08 0.11 B 0.10 0.77 0.13 C 0.11 0.15 0.74
- The consistency of a set of formulas can be defined as: Select one or more: a. There is at least one model for the set. b. There is at least one interpretation on which all the formulas are true. c. There is an interpretation yielding a truth value for all of the formulas in the set. d. There is an interpretation on which some of the formulas are true. e. All of the formulas can be false at the same time.Select one or more: a. We would like to test whether our code work b. We try to avoid a data leakage by using testing data to find a good set of hyper-parameters. c. We would like to get performances from different models (trained from different dataset) to "mitigate" luck. d. We would like to train multiple models and use all of them to make a final model.The questions should be completed with OCaml. Running screenshots should be provided. The background information is given by the picture. Question 1: Provide 5 good test cases each for eval_success_tests and eval_failure_tests, following the format of: let eval_success_tests : ((truth_assignment * formula) * bool) list = [] let eval_failure_tests : ((truth_assignment * formula) * exn) list = [] Question 2: Implement the function eval : truth_assignment -> formula -> bool. let eval (state : truth_assignment) (formula : formula) : bool = raise Not_implemented You are evaluating boolean formulae instead of float arithmetic. You also need to use the correct boolean value for each variable. We recommend using Variable_map.find_opt to perform lookups in the truth assignment. If a variable is needed but does not appear in the truth assignment, you must raise an Unassigned_variable x exception, where x is the unassigned variable. Once again, you may use any functions you want and…
- 1.) We want to build a model to predict the weight (in Ibs) of a car. This prediction will be based on multiple features of the car, such as: "Number of Cylinders", "Miles Per Gallon", "Production Year", etc. To train the model, we are given 1000 examples of cars along with the feature values and class for each car. What technique could we use in this case? Multiple Linear Regression Simple Linear Regression O K-Means Clustering K-Nearest NeighborsInstructions: In the next exercise, you will use a known dataset used as an example for classification problems. Refer to: Index of /ml/machine-learning-databases/balance-scale (uci.edu). The problem has 3 classes and 4 input features. The possible classes are (B: balanced, L: left, R: right), and the 4 input features are: (LW: left weight, RW: right weight, LD: left distance, RD: Right distance). The balance shows up the value ‘B’ when LW + LD = RD + RW. Each raw of the file data is constructed as the following: Class, LW, LD, RW, RD. Example: B, 3, 2, 4, 1. In addition, all the input features might have values 1, ..., 5. For more information refer to website given before. Remark: you are free to propose a preprocessing of the input features, also you’re advised to try different values of the learning rate and observe the training curve. Remark: in your code, you are asked to use python, numpy and matplotlib. You shouldn’t use libraries like scikit, tensorflow, pytorch, or any other…Answer the following questions about the given statement:∀t : Trainers • ∃c : Course • (t,c) ∈Teaches ∧c.time = 2•What does this statement mean?•Is this statement a set or a predicate?•What does the statement evaluate to based on the current system state? Examples for reference:•∃g : Owner • g.name = gymowner ∧g.email = test-There exists an owner with the name gymowner and email test-predicate-false•{c : Course |∃co : Customer • (co,c) ∈Books}-Set of all Courses which are booked by a customer-set-{Boxing,WeightLifting,Yoga1,Wrestling}•{t : Trainer |#{c : Course |(t,c) ∈Teaches}>1}-Set of all Trainers who teach more than 1 class.-set-{Trainer 2}