...Kimberly Glover Mrs. Haraway English Comp II Honors April 24, 2012 Manipulation of the Naïve Cults are not fairly common in this day and age, but most people can recall a time when they were popular. The cults were perceived as very powerful and, at times, dangerous. One such case is the cult known as the Peoples Temple. Even though most people who join cults start off with the best of intentions, they are eventually brainwashed because cults hold tremendous power over their members as a result of charismatic leaders, manipulative persuasion, and extreme isolation. Distinguishing the difference between a cult and a religion is quite hard. Any religion that defies the standards of “mainstream” religions can be considered a cult. This could confuse some people, because most of the popular religions today started out as small religious groups that were seen as cults (Tabor, par. 7). According to Charles Clark, cults have their own unique beliefs and they often differ or challenge religions in society. They may have a leader who sees himself as the chosen one, whereas most religions praise a non-living god who is not the leader of the church. There have been many different cults over the years. Some of the more well known are Peoples Temple led by Jim Jones, Heaven’s Gate led by Marshall Applewhite, and the Branch Davidians led by David Koresh. These cults are remembered more often because of the legacy they left behind. Each of these cults demonstrated a mass...
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...Pattern classification for given problem is posed with serious challenge as on one side the data set is highly imbalanced in favour of B+E against B(So we have to avoid over fitting for generalization) & on the other side wrong classification can have serious consequences in diplomatic relationship between nations. So Our thrust has been to choose between various methods , one with sound justification towards our results & showing how was it better than others . Based on comparative study of various methods we have finally chosen Biased Minimax Probability Machine [1] & we would be proving superiority of our methods over SVM classifier with different parameters which we tried. Besides authors [1] have shown superiority of BMPM over DT, Naive Bayesian Classifier, K-nn classification, & other under/over Sampling methods. Methodology of BMPM: For two class Classification: Let Family {x}, {y} with mean vector & Covariance matrices {x, ∑x }, {y, ∑y} belong to class1 & class2 respectively. Let α be the worst-case accuracy for future data points from family of {x}, and β be the worst-case accuracy for future data points from family of {y}. Depending upon severity of the false positive & true positive rates α, β(Policy variables) it tries to find a maximal hyper plane to separate the two classes [pic] [pic] We can also have Non Linear Classifier by mapping the feature space into suitable higher dimension. The above optimization is changed according to needs, so we would...
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...Assignment 3 – Classification Note: Show all your work. Problem 1 (25 points) Consider the following dataset: ID | A1 | A2 | A3 | Class | 1 | Low | Mild | East | Yes | 2 | Low | Hot | West | No | 3 | Medium | Mild | East | No | 4 | Low | Mild | East | Yes | 5 | High | Mild | East | Yes | 6 | Medium | Hot | West | No | 7 | High | Hot | West | Yes | 8 | Low | Cool | West | No | 9 | Medium | Cool | East | Yes | 10 | High | Cool | East | No | 11 | Medium | Mild | West | Yes | 12 | Medium | Cool | West | No | 13 | Medium | Hot | West | Yes | 14 | high | Hot | East | Yes | Suppose we have a new tuple X = (A1 = Medium, A2 = Cool, A3 = East). Predict the class label of X using Naïve Bayesian classification. You need show all your work. Problem 2 (25 points) Consider the following dataset D. ID | A1 | A2 | A3 | Class | 1 | Low | Mild | East | Yes | 2 | Low | Hot | West | No | 3 | Medium | Mild | East | No | 4 | Low | Mild | West | Yes | 5 | High | Cool | East | Yes | 6 | Low | Hot | West | No | 7 | High | Hot | West | Yes | 8 | Low | Cool | West | No | 9 | Medium | Cool | East | Yes | 10 | High | Hot | East | No | 11 | Medium | Mild | East | Yes | 12 | Medium | Cool | West | No | 13 | High | Hot | West | Yes | 14 | High | Hot | East | Yes | (1) Compute the Info of the whole dataset D. (2) Compute the information gain for each of A1, A2, and A3, and determine the splitting attribute (or the best split attribute)...
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...6.1) Comparison of three numbers Problem is of comparison of values among three values , a very simple problem. Here, the decision making process is done based on the value of the parameters a,b and c. The data types of all these variables are interger. 6.2) Binary search A binary search locates the position of an item in a sorted array. Binary search works by comparing an input value to the middle element of the array. The comparison determines whether the element equals the input, less than the input or greater. When the element being compared to equals the input the search stops and typically returns the position of the element. If the element is not equal to the input then a comparison is made to determine whether the input is less than or greater than the element. Depending on which it is the algorithm then starts over but only searching the top or bottom subset of the array's elements. If the input is not located within the array the algorithm will usually output a unique value indicating this. Binary search algorithms typically halve the number of items to check with each successive iteration, thus locating the given item (or determining its absence) in logarithmic time. A binary search is a dichotomic divide and conquer search algorithm. 6.3) Quadratic problem In Quadratic equation solver problem(called the procedure under test) is chosen. This procedure has three predicates involving both linear and non-linear functions of the input variables. In this there are three...
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...2 Probability To most people, probability is a loosely defined term employed in everyday’s conversation to indicate the measure of one’s belief in the occurrence of a future event. Say, what is the chance of arriving on time if one takes the bus? takes the taxi? However, for scientific purposes, it is necessary to give the word probability a definitive, clear interpretation. One can think of probability as the language in discussing uncertainty. For instance, in tossing a coin (random experiment), the outcomes can either be {H} or {T }. If we know exactly what the outcome of the next trial will be, then we are certain that, say, a {H} will show up next. However, it is impossible to know exactly what is going to happen in reality - uncertainty. Definition. A random experiment is a process leading to at least two possible outcomes with uncertainty as to which will occur. Then, the possible outcomes of a random experiment are called the basic outcomes, and the set of all basic outcomes is called the sample space, S. Examples of random experiment (i) Tossing a coin Basic outcomes: {H}, {T } Sample space, S = {H, T } (ii) Rolling a dice Basic outcomes: {1}, {2}, {3}, {4}, {5}, {6} Sample space, S = {1, 2, 3, 4, 5, 6} (iii) Daily changes in Hang Sang Index Basic outcomes: {up}, {down}, {no change} Sample space, S = {up, down, no change} Definition. An event is a set of basic outcomes, or a collection of some basic outcomes from the sample space, and it is said to occur if the random experiment...
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...Robert Gibbins MATH203-1401A-05 Application of Discrete Mathematics Phase 1 Individual Project January 12, 2014 Part I Demonstrate DeMorgan’s Laws using a Venn diagram: The portions below define 2 sets, and a universal set that exists within the 2 sets.. They state the union and intersection of the 2 sets and the complements of each set. The Venn Diagram gives a visual to give a demonstration of DeMorgan’s law of sets. Union The Union is the combined elements of both sets A and B: A U B = {Addison, Mabel, Leslie, Matt, Rick, Joel} or U = {Addison, Mabel, Leslie, Matt, Rick, Joel} Set A is expressed below in the shaded area of the Venn Diagram: A = {Addison, Leslie, Rick} Set B is expressed below n the shaded area of the Venn Diagram: B = {Mabel, Matt, Joel} Intersection The intersection are the elements both A and B have in common, in this case both softball and volleyball players. The intersection is expressed below and is represented in the shaded section of the Venn Diagram. A ∩ B = {Matt, Rick} Matt Rick Matt Rick Complements The Complement of a set contains everything in the universe minus what is in the set itself. The complement of Set A and Set B are expressed: A’ = {Mabel, Matt, Joel} B’ = {Addison, Leslie, Rick} De Morgan’s Law 1. The first portion of DeMorgan’s law says the complement of the union of sets A and B are the intersection of the...
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...Please provide a short definition of the following: a. Set: A set is a collection of items, referred to as the elements of the set. b. Subset: A subset is a portion of a set c. Proper Subset: a subset that includes some but not all elements of another set d. Compliment of a set: The complement of a set is the set of all elements in the universal set that are not in the initial set e. Union of a set: all elements that are either in one set the other or both. f. Intersection of a set: is the set of all elements that are common to both sets. Solve following problems showing your work: 2. Set X = {3, 7, 11, 21, 39, 43, 567}, Set Y = {1, 3, 6, 8, 11, 42, 567} a. What is the union of Sets X and Y? {1, 3, 6, 7, 8, 11, 21, 39, 42, 43, 567} b. What is the intersection of Sets X and Y+ {3, 11, 567} c. Create your own set Z that is a proper subset of Set X. Set Z = {3, 7, 11, 21, 39, 43} 3. Let Set 1 be the entire alphabet. Let Set 2 = {m, n, o, p, q, r} a. What is the complement of Set 2 in Set 1? 2’ = {a,b,c,d,e,f,g,h,I,j,k,l,s,t,u,v,w,x,y,z} b. Set 3 = {n, o, p, q}. Is Set 3 a proper subset of Set 2? Explain your reasoning. Yes, a proper subset is a subset that includes some but not all elements of another set 4. Take out a coin for the following problems: a. Suppose you are going to flip a coin once. What is the set of possible outcomes for this? S = {Heads, Tails} b. Suppose you are going to flip a coin twice. What is the set of possible...
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...The world is always changing, which brings about changes in data and theories. Some people overlook changes in concepts due to their personal fixed perceptions. They’re positive that their credence is precise. Many people have the tendency to believe that their perceptions of human nature and the world are correct, regardless of if the data present contradicts their understanding (example of Belief Perseverance). People’s beliefs are often influenced by those surrounding them, their past experiences (implicit and explicit memories) and their observations. However, everything is not always as it seems, so it’s skeptical to follow the phrase “seeing is believing” (example of Naïve Realism). Naïve Realism and Belief Perseverance are two of many factors that contributes to the notion Confirmation bias. This is when people attempt to prove their theories to be correct, they only present evidence that supports and justifies their beliefs. People like such portray overconfidence, and make an effort to convince others that what they know is correct. These individuals are under the impression that what they’ve known previously is a fixed concept, when in reality; any concepts that they’ve come to learn of can be refuted with new data and observations. People can’t always use their...
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...Touro University International Quantitative Reasoning (BUS306) “Quantitative Reasoning” Module 1 Case Assignment Professor: Date: 1. Set X = {5, 7, 11, 13, 16,19}, Set Y = {1, 2, 5, 13, 19} a. What is the union of Sets X and Y? X u Y = {1,2,5,7,11,13,16,19} b. What is the intersection of Sets X and Y X ⊂ Y = {x|x ∈ X and x ∈ Y} c. Create your own set Z that is a subset of Set X. Z u X 2. Let Set 1 be the entire alphabet. Let Set 2 = {a,b,c,d,e} a. What is the complement of Set 2 in Set 1? (1 u 2)’ = 1' n 2’ b. Set 3 = {a,b,c}. Is Set 3 a proper subset of Set 2? Explain your reasoning. Yes, set 3 is a proper subset of set 2 is an infinite set 3. Take out a coin for the following problems: a. Suppose you are going to flip a coin once. What is the set of possible outcomes for this? Either you get heads or tails S = {H,T} b. Suppose you are going to flip a coin twice. What is the set of possible outcomes for this? Again either you get Heads or Tails S x S + (H,H), (H,T), (T,H), T,T) c. If flip a coin twice, what are the chances that you will get one head and one tail (i.e. one in three, one in four, etc.)? Use your answer to the question 3b to get your answer. Here we are getting a fifty fi=fty chance of getting...
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...Quantitative Reasoning 1. Create two sets. Set A will be the list of the five items you personally need to buy the most (essential items). Set B will be the list of the five items that you want to buy the most (fun stuff). ANSWER: A = {CAR, GAS, WATER, FOOD, HOUSE} B = {CAR, COMPUTER, IPOD, HOUSE, TV} 2. List the items in Set A and Set B, and also list or state the items in the union and in the intersection of Set A and Set B. ANSWER: UNION = {CAR, GAS, WATER, FOOD, HOUSE, COMPUTER, IPOD, TV} INTERSECTION = {CAR, HOUSE} 3. Now assume that the prices of the items in your set A are 20, 40, 60, 70 and 80. Assume that the prices of the items in your set B are 90, 120, 30, 60 and 40. Note: if you have one or two identical items in both sets, then assume that the prices of the identical items are the same as the prices that appear in set A (instead of having two different prices to the same item.) ANSWER: A = {(CAR, $20) (GAS, $40) (WATER, $60) (FOOD, $70) (HOUSE, $80)} B = {(CAR, $20) (COMPUTER, $90) (IPOD, $120) (HOUSE, $80) (TV, $30)} 4. What will the total cost of Set A be if it contains one unit of each item? ANSWER: $270 5. What will the total cost of the union set be if it contains one unit of each item? ANSWER: UNION SET = $20 + $40 + $60 + $70 + $120 + $80 +$30 = $420 6. What will be the total cost of the intersection? ANSWER: ...
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...Applications Of Discrete Mathematics 7/8/2014 Phase 1 Discussion Board 2 To describe the notion of union and intersection we must first start with a set. A set can be numbers, objects, people etc. When you have sets of things, they can be combined to create a union or have elements in common. For example, if a company were looking for an employee within the database system they could search using last names. Say department A has Smith, Jones, Brown, Doe. Department B has Doe, White, Turner, Smith. The union of these sets would be written as follows: A U B = {Jones, Brown, Doe, Smith, White, Turner} The sets intersect with the two names in common, Doe and Smith. That would be written as: A n B= {Doe, Smith} The logical “and” and the logical “or” are important for database retrieval and flowcharts to help the system or reader to understand which way they need to go to seek out the information requested. Simple and compound statements help understand this notion. To help understand this let’s refer back to the original example. If the person searching the company database wanted to find a specific employee they would search for the last name and maybe first initial. This would take the search from a simple statement to a compound statement. The database would then need to search for the last name first and when it found the right name, Smith, it would then need to search for the first initial...
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...Amanda Raby 5/18/16 “Logic and Set Theory” Part # 1 The intersection gives only what the two sets have in common. The union of two sets is the set of elements which are in either set. The intersection of two sets is the set of elements which is in both sets. Make sense right? At times there will not be any intersection at all, this would be called an empty or null set. The intersection gives you only what the two sets have in common whereas the union combines the sets. With the union we can retrieve records from both database sets, being able to access all of each set of records but when using the intersection of the database sets you can only access the records that meet both conditions. Some examples may include the following (Something I can think of): After doing some reading I figure that most everyday things we encounter is ran through a database. When you access a database, often you want to recover only records with certain features. The records with these features can be treated as a set. For example, one set is all children born in the state of Maryland and the other set is all children born with Red hair in the U.S. When you use the union of both sets we include all children in the state of Maryland and all children born with Red hair nationwide. This will includes all of both sets, but when you...
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...A Naï Sahib in India ve Weiting Xu A Naï Sahib in India ve Student Name: Weiting Xu Student ID: 212242624 Course Director: Indira Somwaru Course Name: Applied Cross Cultural Management Course Code: INTL 3350 [A] Date: Wednesday, October 8th, 2014 Page 0 of 12 Image Credits: http://www.almrsal.com/post/122253/detroit-resources A Naï Sahib in India ve Weiting Xu INTRODUCTION Dear Executive Board of Aspen Automative, In the report enclosed, I have gone through an exhaustive review of the new acquisition between Aspen Automative (Aspen) and Bindi Break Company (Bindi) involving Managing Director, Brian Moseley, and Bindi‟s management team. Mr. Moseley is an intelligent individual with post-secondary degrees from top universities and previous international management experience. The decision made by the executive board to send Mr. Moseley to India to increase efficiency and profitability of Bindi was not a mistake but in fact a cultural misunderstandings concern. Throughout the report, I will utilize the information you have given me to provide an objective analysis on each situation and how to resolve the check-mate both parties are currently at. Furthermore, I will provide recommendations on how to proceed further along with general advice for future dealings internationally. Should you have any questions or concerns, feel free to contact me. Best Regards, W.Xu Weiting Xu Cultural Consultant, InterContinental Inc. Page 1...
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...APPENDIX 1 OVERVIEW OF THE TERM PAPER PROJECT……………..12 REFERENCES……………………………………………………………………..13 introduction The purpose of this term paper is to analyze accuracy of the analysts’ forecasts during 2012 on the Finnish stock markets, focusing on EPS and sales forecasts. We are using the forecasts from January 2012 which could be quite far from the actual for example comparing to the forecasts of December 2012. We are going to see if the analysts’ forecasts differ much from those of the Naïve model. According to the article “Comparative Analysis of European Earnings Forecasts” by Capstaff, Paudyal and Rees (Journal of Business Finance & Accounting, 28(5) & (6), June/July 2001, 0306-686X), the bias in analysts’ forecasts is positive in all (European) countries and the naïve forecast bias is negative in all countries. Moreover, they state that analysts’ forecasts are substantially more accurate than the naïve model. We find this investigation interesting because it is nice to know if the Naïve model is better than the analysts’ forecasts. In that case we could consider whether there is a role for the analysts at all. Also it is nice that the data is Finnish so it might be that there is not much investigation done before. * 2 DATA ANALYSIS Table 1 | Minimum | Maximum | Mean | Median | St.deviation | Skewness | Kurtosis | EPS2012 | -0,900 | 4,658 | 0,658 | 0,380 | 0,878 | 1,625 | 4,264 | EPS2011 | -0,520 | 4,240 | 0,692 | 0,410 | 0...
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...Bella De Freitas De Freitas 1 English 1 Ms. Cutright 29 May 2018 Impulsive and Naive Decisions When put in a conflict or a tough situation, people make impulsive and naive decisions. Many novels use a character who demonstrates these qualities. In the tragedy, Romeo and Juliet, Romeo’s impulsive and naive behavior leads to many consequences and deaths. Romeo makes an impulsive decision to kill Paris and himself. When Romeo encounters Paris at the Capulet’s tomb, he tells him, “By heaven, I love thee better than myself,/ For I come hither armed against myself”(5.3.64-65). Romeo‘s impulsiveness was fueled by his love for Juliet. His actions were not one of a rational person but of someone who carried a great...
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