Rock Algorithm

In: Computers and Technology

Submitted By DonOzone
Words 838
Pages 4
Introduction Clustering in data mining, is useful in discovery of distribution patterns in underlying data. Our interest is in clustering based on non-numerical data-categorical or Boolean attributes. An example of hierarchical clustering algorithm used in sample data is ROCK (RObust Clustering using linKs). The clustering technique is useful for grouping data points such that a single group or cluster have similar characteristics while different groups are dissimilar. ROCK belongs to the class of agglomerative hierarchical clustering algorithms. OCK algorithm has mainly 3 steps namely, ‘Draw random sample’, ‘Cluster with links’, ‘Label data in disk’ the steps are described in the following diagram: ROCK’s hierarchical algorithm accepts as input the set S of N sample points to be clustered, and the number of desired clusters K. The first step in the procedure is to compute the number of links between pairs of points. Initially each point is separate cluster. For each cluster i, we build a local heap q[i] and maintain the heap during the execution of the algorithm. Q[i] contains every cluster j such that link[i,j] is non-zero. The clusters j in q[i] are ordered in the decreasing order of the goodness measure with respect to I, g(i,j). In addition to the local heaps q[i] for each cluster I, the algorithm also maintains an additional global heap q that contains all the clusters. Furthermore, the clusters in q are ordered in the decreasing order of their best goodness measures. Thus, g(j, max(q[j])) is used to order the various clusters j in q, where max(q[j]), the max element in q[j], is the best cluster to merge with cluster j. At each step, the max cluster j in q and the max cluster q[j[ are the best pair of clusters to be merged. Example program in R is as follows: For every point, after computing a list of its neighbors, the algorithm considers all…...

Similar Documents

Rocks

...ultimate legal question of nonobviousness, beyond stating that it depends on the identified underlying factual considerations.32 Identifying the differences between the patent claims at issue and the prior art is one question. Determining the amount of inventiveness a person of ordinary skill in the art would need to bridge these differences, and whether such an amount meets the nonobviousness threshold, are separate issues. The Supreme Court’s application of its new nonobviousness framework to the facts in Graham likely exacerbated the problem created by the lack of a definitional basis for the nonobviousness standard. The patent at issue in Graham concerns a spring for a plow shank, which allows the plow shank to move upwards when it hits rocks or other obstructions in the soil, thereby reducing damage to the plow.33 The Court engaged in a detailed factual analysis of the relevant prior art in plow shanks and the differences between the prior art and the claims at issue.34 The Court did not, however, analyze the Graham, 383 U.S. at 17. Sakraida v. Ag Pro, Inc., 425 U.S. 273, 280 (1976); Graham, 383 U.S. at 17. 30 Graham, 383 U.S. at 17-18. The Federal Circuit has subsequently held that it is “error to exclude [secondary consideration] evidence from consideration.” Stratoflex, Inc. v. Aeroquip, 713 F.2d 1530, 1539 (Fed. Cir. 1983). 31 Sakraida, 425 U.S. at 280; Graham, 383 U.S. at 17. 32 FED. TRADE COMM’N, supra note 10, ch. 4, at 9 (“Although the Court lists the key......

Words: 31121 - Pages: 125

Planning Algorithm

...Module 9 Planning Version 2 CSE IIT,Kharagpur Lesson 25 Planning algorithm - II Version 2 CSE IIT,Kharagpur 9.4.5 Partial-Order Planning Total-Order vs. Partial-Order Planners Any planner that maintains a partial solution as a totally ordered list of steps found so far is called a total-order planner, or a linear planner. Alternatively, if we only represent partial-order constraints on steps, then we have a partial-order planner, which is also called a non-linear planner. In this case, we specify a set of temporal constraints between pairs of steps of the form S1 < S2 meaning that step S1 comes before, but not necessarily immediately before, step S2. We also show this temporal constraint in graph form as S1 +++++++++> S2 STRIPS is a total-order planner, as are situation-space progression and regression planners Partial-order planners exhibit the property of least commitment because constraints ordering steps will only be inserted when necessary. On the other hand, situation-space progression planners make commitments about the order of steps as they try to find a solution and therefore may make mistakes from poor guesses about the right order of steps. Representing a Partial-Order Plan A partial-order plan will be represented as a graph that describes the temporal constraints between plan steps selected so far. That is, each node will represent a single step in the plan (i.e., an instance of one of the operators), and an arc will designate a temporal......

Words: 3041 - Pages: 13

The Rock

...English 1301 21 Feb 2013 The Rock He is a three-time world wrestling federation champion and a two time intercontinental champion. He was born on May 2, 1972 is 6’5 and weighs 275 pounds. He goes by the name Dwayne Johnson, calls himself the “People’s Champion” and otherwise known as “The Rock.” Other than having the pretty face that Hollywood was looking for, The Rock had to go through many steps as an “actor” before he became well known. However, the rock graduated from the University of Miami as an all -American Football player. Right away, he was entered into the realm of entertainment. This in turn was called a secondary effect because The Rock being a football player was entertainment and attracted the media’s attention. He was ready to enter the world of a celebrity and a star. The public considers the Rock to be a celebrity being that he has gone from music, to commercials, to sports, and journalism. He has starred on Saturday Night Live, That 70’s Show, and will soon be featured in the sequel to “The Mummy” as the Scorpion King. He is an entertainer who loves performing for the crowd. As he himself said, “Always entertaining the fans and knowing that I’m entertaining them-that’s the goal, to entertain the fans and noth compares to that.” Each time he appears somewhere knew it adds to his popularity more and more. You start to conform to this so- called “reality.” The Rock plays many different roles and has many different names that one might wonder which he...

Words: 717 - Pages: 3

Algorithms Notes

...DAG Topological Sort O(V+E) -performed on directed acyclic graph Linear ordering of all its vertices such that if G contains an edge (u,v) then u appears before v in the order. 1. call DFS(G) to compute finishing times v.f for each vertex v 2. as each vertex is finished insert it onto the front of a linked list 3. return the linked list of vertices 4. Lecture 5 (01/28) Posted on: Monday, January 28, 2013 Topics: Strongly Connected Components, Activity Selection Reading: CLRS (22.5, 16.1), KT (4.1) Scheduling Probelem Set of n activities which can be served only one at a time, each with start time s and finish time f Selecct a maximum-size subset of mutually compatible activities (meaning no overlap) GREEDY ALGORITHM Note that putting the job with the earliest finish time allows for the most amount of jobs to follow, because it allows the machine to have the most possible time to get to other jobs Take job with lowest finish time, then reduce set to all job that don’t overlap, then choose lowest finishing time, recursively. * Lecture 6 (01/30) Posted on: Wednesday, January 30, 2013 Topics: Activity Selection, Coloring Interval Graphs, Scheduling Reading: CLRS (16.1, 16.2), KT (4.1, 4.2) * Lecture 07 (02/04) Posted on: Wednesday, February 6, 2013 Topics: Minimizing Maximum Lateness, Sorting (Insertion Sort, Merge Sort, Quick Sort) Reading: CLRS (Chp 2, 7.1, 7.2), KT (4.2) Insertion sort Starting from the second element as key......

Words: 5019 - Pages: 21

Algorithms

...Algorithms Assignment 1 Kent Vuong Table of Contents Question 1 3 Machine Code (First Generation or 1GL) 3 Assembler (Second Generation or 2GL) 3 Procedural (Third Generation or 3GL) 3 Non-Procedural (Fourth Generation or 4GL) 4 Object Orientated 4 Describe the purpose and functions of an OS with the following terms 4 Scheduling 4 Managing Concurrency 4 Managing Memory 4 Managing Devices 5 File Systems 5 Describe the purpose of each of the following utility software programs. 5 File Compression 5 Defragmenter 5 Anti-Virus 5 Anti-Malware 5 What is application software, give three examples 5 What are the software licensing requirements for the following types of software 6 Freeware 6 Open Source 6 Shareware 6 Question 1 Machine Code (First Generation or 1GL) Machine Code is the Language that the Computer understands and reads, following the precise instructions, which is sometimes the problem with computers and the relaxed non-procedural human brain. The MIPS architecture provides a specific example for a machine code whose instructions are always 32 bits long. The general type of instruction is given by the op (operation) field, the highest 6 bits. J-type (jump) and I-type (immediate) instructions are fully specified by op. R-type (register) instructions include an additional field function to determine the exact operation. Assembler (Second Generation or 2GL) Assembler is a program which makes object codes by encoding...

Words: 1019 - Pages: 5

382 Algorithms

...CSC 382, Analysis of Algorithms Group Project For this project you need to make groups of 3-6 people and choose one of the following topics. Most of these topics require you to write a short paper and present it in class (20 points). For those you have the option to just submit a paper and not present for only 10 points. A list of topics: 1. Linear Programming 2. Approximation Algorithms 3. Max-Flow Min-Cut 4. Cryptography: Asymmetric Encryption 5. Complexity Theory 6. Programming Project: Implementing Algorithms, Comparing Running times (10 points, no presentation) For some topics you can find information in the course textbooks (and other textbooks). For the rest, you must research on your own - but I am willing to give suggestions if I have any. You may suggest another topic as well, but I need to approve it. Requirements Each paper is expected to be 3-5 pages long (single-spaced and at 11pt) and it should include references to your sources (which should be more than just Wikipedia). As long as the paper is complete and well-written, the length requirements should not be too important. However, more than 5 pages would be an overkill and less than 3 might not let you give the necessary information and explanations. As for the actual contents of the paper, you should address your classmates, who will receive a copy of the paper in class and before your presentation. You should explain the topic you have selected and give an appropriate 1 2 example. The specifics may differ...

Words: 796 - Pages: 4

Gnetic Algorithms

...Genetic Algorithms Basic Genetic Algorithm – Flow Chart 1. Initial Population 1. Initial Population ON ON | | GENERATE RANDOM POPULATION (POSSIBLE SOLUTIONS) | 2. Fitness Evaluation 2. Fitness Evaluation 3. Selection 3. Selection | | EVALUATE THE FITNESS OF EACH (BASED ON THE FITNESS FUNCTION) | | | CHOOSE PARENT FACTORS (BETTER FITNESS = BETTER CHANCE) | 4. Crossover 4. Crossover 5. Mutation 5. Mutation | | CROSSOVER THE PARENT TRAITS TO FORM NEW CHILDREN. (PROBABILITY) | | | MUTATION PROBABILITY APPLIED (MAINTAINS GENETIC DIVERSITY) | Acceptable? Acceptable? | | IF OPTIMIZATION CONDITIONS ARE NOT MET(REPEAT STEPS 2-5) * OR | Yes Yes End Process End Process | | IF THE MAXIMUM GENERATIONS ARE MET (TERMINATE) * OR | | | IF SATISFACTORY FITNESS LEVEL IS REACHED (END THE PROCESS) | KEY TERMS * INDIVIDUAL Any possible solution to the problem at hand, usually expressed in binary code * POPULATION Group of all individuals * CHROMOSOME Blueprint for an individual usually expressed in binary code. (Ex: 011011) * GENE An individual value in a chromosome, usually expressed as a “1” or “0” * PARENTS An original “individual” solution in the GA process that has passed the fitness function * CHILDREN A new solution to the problem formed through crossover and mutation from the parent solutions * SEARCH SPACE All possible solutions to the......

Words: 261 - Pages: 2

Kolmogorov Algorithm

...CSC 435 DESIGN AND ANALYSIS OF ALGORITHM GROUP THREE(3) ASSIGNMENT THE KOLMOGOROV COMPLEXITY ALGORITHM Computer Science: FMS/0704/11 FMS/0707/11 FMS/0720/11 FMS/0721/11 FMS/0728/11 Computing-with-Accounting: FMS/0818/11 FMS/0643/11 FMS/0749/11 FMS/0722/11 FMS/0729/11 FMS/0741/11 FMS/0829/11 FMS/0784/11 FMS/0812/11 FMS/0652/11 Kolmogorov complexity In algorithmic information theory (a subfield of computer science and mathematics), the Kolmogorov complexity (also known as descriptive complexity, Kolmogorov–Chaitin complexity, algorithmic entropy, or program-size complexity) of an object, such as a piece of text, is a measure of the computability resources needed to specify the object. It is named after Andrey Kolmogorov, who first published on the subject in 1963. For example, consider the following two strings of 32 lowercase letters and digits: abababababababababababababababab 4c1j5b2p0cv4w1x8rx2y39umgw5q85s7 The first string has a short English-language description, namely "ab 16 times", which consists of 11 characters. The second one has no obvious simple description (using the same character set) other than writing down the string itself, which has 32 characters. More formally, the complexity of a string is the length of the shortest possible description of the string in some fixed universal description language (the sensitivity of complexity relative to the choice of description language is discussed below)...

Words: 3373 - Pages: 14

Algorithm

...Design and Analysis of Computer Algorithm Assignment 2 Name: Boyu Zhang UTD-ID: 2021226566 Email:bxz140830@utdallas.edu Contents Problem 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Problem 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Problem 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Problem 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Problem 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Problem 6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Problem 7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Problem 8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11 Problem1 This problem can solution by Dial’s algorithm in the lesson six. We can set up W+2 buckets with the labels of 0, 1, …, W, . Then we carry out the following steps: (a). Initial the buckets with node S be in the bucket 0 and all other nodes be in the bucket . (b). then select the node with the minimum temporary distance label. For the first time, it should be the source node S in the bucket 0. (c). Update the buckets information. Then some node should be moved from the bucket  to the corresponding distance bucket. (d). Remove the selected node from the bucket. Then repeat step 2 and 3 until there is no non-empty bucket.......

Words: 726 - Pages: 3

Rocks

...Rock Report Exercise Due Date: 4/1/2014 Name: Rianne Richter Class: 1121k Grade: /35 After you have finished Lab Exercises 4, 5, and 7, complete the following questions. You may have to refer to the exercises for assistance to locate specific answers. 1. Match the rock type with the correct statement describing its formation. (3 point). ❖ Found where the atmosphere or liquid water causes erosion and movement of rock pieces. Metamorphic Formation ❖ Found mostly near convergent tectonic plate boundaries where the P/T condition can be very high. Sedimentary Formation ❖ Found in places where the interior is so hot that rock melts and tehn cools again to form new rock. Igneous Formation 2. List the texture and mineral composition of each of the following rocks. (5 points). Granite: Schistosity; Quartz, K-feldspars, biotite. Marble: Non-foliated; Calcite. Sandstone: Clastic; Quartz, feldspare. Gneiss: Compositional Banding; Diorite or granite. Shale: Layered, fine-grained; Quartz. 3. Where would you expect to find the coarser textured igneous rocks, in a laccolith or in a lava flow? Why? (2 points) A laccolith, because rocks that are found in a lava flow cool too fast to form course faces. 4. Which of...

Words: 762 - Pages: 4

Vwap Algorithm

...Competitive Algorithms for VWAP and Limit Order Trading Sham M. Kakade Michael Kearns Computer and Information Science University of Pennsylvania Computer and Information Science University of Pennsylvania kakade@linc.cis.upenn.edu mkearns@cis.upenn.edu Yishay Mansour Luis E. Ortiz Computer Science Tel Aviv University Computer and Information Science University of Pennsylvania mansour@post.tau.ac.il leortiz@linc.cis.upenn.edu ABSTRACT We introduce new online models for two important aspects of modern financial markets: Volume Weighted Average Price trading and limit order books. We provide an extensive study of competitive algorithms in these models and relate them to earlier online algorithms for stock trading. Categories and Subject Descriptors F.2 [Analysis of Algorithms and Problem Complexity]: Miscellaneous; J.4 [Social and Behavioral Sciences]: Economics General Terms Algorithms, Economics Keywords Online Trading, Competitive Analysis, VWAP 1. INTRODUCTION While popular images of Wall Street often depict swashbuckling traders boldly making large gambles on just their market intuitions, the vast majority of trading is actually considerably more technical and constrained. The constraints often derive from a complex combination of business, regulatory and institutional issues, and result in certain kinds of “standard” trading strategies or criteria that invite algorithmic analysis. One of the most......

Words: 9064 - Pages: 37

On the Rocks

...Executive Summary: On the Rocks is a soft drinks bar which would be serving its customers with the most stimulating and exotic drinks that they have never tasted before. Our chilled and invigorating drinks would sure refresh the drinkers. On the Rocks provides fizzy drinks which are a combination of various other soft drinks along with other juices and ingredients. On the Rocks promises their customer by providing them with the best quality new flavored fizzy drinks at the fastest possible time. Our combination of different juices and soft drinks would surely make the drinkers feel fanatical. We have set up our business at different shopping malls and departmental stores. We are also available for weddings and parties. We are a small business who presents the drinks as we receive the customer’s order on the counter. Within no time our customers have their drink in their hands. We have basically focused the youngsters and kids who mostly enjoy fizzy drinks and like to try out new flavors. We have set up our business at the shopping malls and departmental stores as we can receive customers at the hub of the mall. We have done our marketing through flyers, brochures, and most probably word to mouth. We have Our competitors are the other stalls which are the hub of the shopping malls like the gola wala, the magic corn, ice cream, etc. We are currently working 10 hours, seven days a week. We intend to provide customer satisfaction in every possible way. In the near future, we......

Words: 1926 - Pages: 8

Algorithm

...1. Illustrate the operation of Radix_sort on the following list of English words: cow, dog, seq, rug, row, mob, box tab, bar ear, tar, dig, big, tea, now, fox. ANSWER: It is a sorting algorithm that is used to sort numbers. We sort numbers from least significant digit to most significant digit. In the following array of words, three is the maximum number of digits a word has, hence the number of passes will be three. In pass 1, sort the words alphabetically using first letter from the right. For eg, tea has “a” as the last letter, hence it comes first, similarly mob which has “b” as the last letter comes second. In this way the remaining words are sorted. In pass 2, sort the words alphabetically using second letter from the right. For eg, tab has “a” as its middle letter which comes first, then comes bar and so on. In pass 3, sort the words alphabetically using third letter from the right. For eg, bar has “b” as its first letter from left and since no word starts with “a”, bar will appear first. Similarly, big, box, cow and so on. UNSORTED ARRAY | PASS 1 | PASS 2 | PASS 3(SORTED ARRAY) | cow | tea | tab | bar | dog | mob | bar | big | seq | tab | ear | box | rug | rug | tar | cow | row | dog | tea | dig | mob | dig | seq | dog | box | big | dig | ear | tab | seq | big | fox | bar | bar | mob | mob | ear | ear | dog | now | tar | tar | cow | row | dig | cow | row | rug | ...

Words: 1470 - Pages: 6

Rocks

...water bodies. | Arkose is a detrital sedimentary rock, specifically a type of sandstone containing at least 25% feldspar. | Syenite a coarse-grained gray igneous rock composed mainly of alkali feldspar and ferromagnesian minerals. | Tephrite is an igneous, volcanic (extrusive) rock, with aphanitic to porphyritic texture. | Monolith a large single upright block of stone, especially one shaped into or serving as a pillar or monument. | Peridotite is a dense, coarse-grained igneous rock, consisting mostly of the minerals olivine and pyroxene. | Amphibolite is a coarse-grained metamorphic rock that is composed of amphibole minerals and plagioclase feldspar. | Magnetite is a mineral and one of the three common naturally-occurring oxides of iron. | Rhyolite is an igneous, volcanic rock, of felsic (silica-rich) composition (typically > 69% SiO2 | Pelite is a term applied to metamorphic rocks derived from a fine-grained sedimentary protolith. | Turbidite a type of sedimentary rock composed of layered particles that have originated from the oceans. | Siltstone is a sedimentary rock which has a grain size in the silt range, finer than sandstone and coarser than claystones. | Pumice is a light-colored, extremely porous igneous rock that forms during explosive volcanic eruptions. | Limestone is a sedimentary rock composed primarily of calcium carbonate (CaCO3) in the form of the mineral calcite. | Troctolite is a mafic intrusive rock type. It consists essentially of major but......

Words: 305 - Pages: 2

Greedy Algorithm

...GREEDY ALGORITHM A greedy algorithm is a mathematical process that looks for simple, easy-to-implement solutions to complex, multi-step problems by deciding which next step will provide the most obvious benefit. Greedy algorithms are similar to dynamic programming algorithms in that the solutions are both efficient and optimal if the problem exhibits some particular sort of substructure. A greedy algorithm builds a solution by going one step at a time through the feasible solutions, applying a heuristic to determine the best choice. A heuristic applies an insight to solving the problem, such as always choose the largest, smallest, etc. Such algorithms are called greedy because while the optimal solution to each smaller instance will provide an immediate output, the algorithm doesn’t consider the larger problem as a whole. Once a decision has been made, it is never reconsidered. Greedy algorithms work by recursively constructing a set of objects from the smallest possible constituent parts. Recursion is an approach to problem solving in which the solution to a particular problem depends on solutions to smaller instances of the same problem. Advantages of greed algorithm * Always taking the best available choice is usually easy. * It usually requires sorting the choices. * Solutions to smaller instances of the problem can be straightforward and easy to understand. * Repeatedly taking the next available best choice is usually linear work. * But......

Words: 387 - Pages: 2