... Fundamentals of DataStructuresin C + + His publications and research interests are in VLSI design automation, parallel computing, and applied algorithms anddatastructures His data structures- related ... i and n) that are not included in the estimate Other operations such as initializing positionOfCurrentMax and incrementing the for loop index i are also not included in the estimate int max(int ... 25-1 Cuttings Approximate Geometric Query Structures Christian A Duncan and Michael T Goodrich 26-1 GeometricandSpatialDataStructuresinExternal Memory...
... logger from tampering with events occurring before a Byzantine failure by rolling back the log and creating a new fork Membership auditing is required to look up and examine old events in the log Itkis ... software and hardware techniques used by databases to speed up queries may be used, including faster or higher throughput storage systems or partitioning the dataand storing it in- memory across ... supported, in part, by NSF grants CNS-0524211 and CNS-0509297 References [1] ACCORSI , R., AND H OHL , A Delegating secure logging in pervasive computing systems In Security in Pervasive Computing (York,...
... C.L Giles and M Gori, Adaptive Processing of Sequences andDataStructures New York, Springer, 1998 A.C Tsoi, “Gradient Based Learning Methods,” Adaptive Processing of Sequences andData Structures, ... set of training (input-output) examples Each input-output example can be formed in a tree data structure consisting of a number of nodes with their inputs and target outputs Each node’s inputs are ... processing of data structure GENETIC EVOLUTION STRUCTURES FOR PROCESSING OF DATA The genetic evolution neural network introduces an adaptive and global approach to learning, especially in the reinforcement...
... full-text indexing data structure field includes: indexes inexternalmemory (for suffix array[35, 105], for suffix tree[10], for FM-index[51], andin general [57]), parallel and distributed indexes[97], ... The expected running time andmemory to find the meaningful alignment using DAWG is bounded by the expected number of distinct substrings in S and substrings in P in which meaningful alignment ... substring, finding repetitions in a text, searching for a square, computing the longest common substring of a finite set of strings, on-line substring matching, and approximate string matching [3, 56,...
... writing large programs, the datastructures that maintain the datain your program govern the space and time consumed by your running program In addition, large programs take time to write Using ... meet the demands of the user 1.9 Who Is the User? When implementing datastructures using classes and interfaces, it is sometimes hard to understand why we might be interested in hiding the implementation ... points within the window Suppose, also, that we have methods for drawing line segments, say, using the Line object How might we implement a rectangle—called a Rect—to be drawn in the drawing window?...
... describing the lowest point The number of students hit a trough/plunged to a trough of 2000 For describing a fluctuation The number fluctuated between and The number fluctuated wildly around and ... The number fluctuated between and The number fluctuated wildly around and Some words for describing “approximately” About/around/approximately/well over/roughly ...
... OracleXmlType and Connection Dependency Updating XMLType Datain the Database Server Updating with DataSet, OracleDataAdapter, and OracleCommandBuilder Updating with OracleCommand and ... contains: Chapter 1, "Introducing Oracle Data Provider for NET" Provides an overview of Oracle Data Provider for NET Chapter 2, "Installing and Configuring" Describes how to install Oracle Data ... without having to make changes to their application code I Support for BINARY_FLOAT and BINARY_DOUBLE datatypes in the database ODP.NET supports the new database native types BINARY_FLOAT and BINARY_DOUBLE...
... (Closest Point Theorem) Let A be a nonempty, closed convex set in IRn and x ∈ A Then, there exists a unique point y ∈ A with minimum distance from x Furthermore, y is the minimizing point, or closest ... Duality for sets and functions Closest point theorem A well-known geometric fact is that, given a closed convex set A and a point x ∈ A, there exists a unique point y ∈ A¸ with minimum distance ... for sets and functions Supporting hyperplane A convex set has a supporting hyperplane at each boundary point Theorem (Supporting Hyperplane) Let S be a nonempty convex set in IRn , and let x...
... combination of x and y The line passing through two points x and y is defined by {αx + (1 − α)y | α ∈ IR} 1) Geometrically, A is affine if it contains the line passing through each pair of its points ... contained in C The interior of C is denoted by intC From this definition, we have x ∈ int C ⇔ ∃δ > such that B(x, δ) ⊆ C Many nonempty convex sets have an empty interior For example, in IR2 , int ... sets and functions Relative Interior of a Convex Set The interior of a subset C of IRn is the union of all open sets (of IRn ) contained in C Since any union of open sets is open, the interior...
... Transformations and Difficulties—Variables, Data, and Information Much of this discussion has pivoted on information—information in a data set, information content of various scales, and transforming information ... concept of information is crucial to data mining It is the very substance enfolded within a data set for which the data set is being mined It is the reason to prepare the data set for mining—to best ... expose the information contained in it to the mining tool Indeed, the whole purpose for mining data is to transform the information content of a data set that cannot be directly used and understood...
... Enhancing and enriching the data Looking for sampling bias Determining data structure Building the PIE Surveying the data Modeling the data 3.3.1 Stage 1: Accessing the Data The starting point ... PIE-I and PIE-O modules 3.1.2 Step 2: Survey the Data Mining includes surveying the data, that is, taking a high-level overview to discover what is contained in the data set Here the miner gains ... relationships as the training data set, but the two data sets contain noise relationships that are different During training, if the predictions are tested in both the training and test data sets, at first...
... particularly in insurance and financial data sets Modeling insurance data, as an example, frequently involves dealing with what look like outliers, but are in fact perfectly valid values In fact, ... embellishing or expanding the existing data set without adding external sources Feature extraction is one way of enhancing data Another method is introducing bias for a particular purpose Adding bias ... tree showing interaction between AGE_INFERR and the most strongly interacting variable, DOB_YEAR (a) Graphing the detected interaction between AGE_INFERR and DOB_YEAR (b) Exploring the data set...
... for numerating the alphas, but also for conducting the data survey and for addressing various problems and issues indata mining Becoming comfortable with the concept of data existing in state ... holder, domain expert, and miner The next actions need to expose information to modeling tools and fix various problems in the variables, andin the data set as a whole The next chapter begins this ... Inferential modeling would still be of use to discover what was in the data It might provide a useful model of a very large data set and give useful insights into related structures No training...
... difficulties in determining density just by looking at the number of points in a given area, particularly if in some places the given volume only has one data point, or even no data points, in it If ... points Figure 6.6 Finding the distance between two points in a 2D state space Just as with finding the length of the longest straight line that can be drawn in state space, so too this finding ... shortcoming is to divide up the area to be searched, and to find a nearest neighbor in each division, as shown in Figure 6.9(b) Still using four neighbors, dividing space into quadrants and finding...
... of the information pattern in the population that the modeling tool is not going to be exposed to during training The model can’t see them during training because they aren’t in the training sample ... surveying and mining Please purchase PDF Split-Merge on www.verypdf.com to remove this watermark Chapter 7: Normalizing and Redistributing Variables Overview From this point on in preparing the data, ... during data preparation It has two components: the PIE-Input component (PIE-I) that dynamically takes a training-input or live-input data set and transforms it for use by the modeling tool, and...
... building a useful model In one particular instance, data had been assembled into a data warehouse The architects had carefully prepared the data for warehousing, including replacing the missing ... straight line Linear regression involves finding the appropriate a and b values to use in the expression for a straight line that make it best fit through the points in state space The linear regression ... collapsing them into a single value (“clipping”) Softmax scaling does the least harm to the information content of the data set Yet it still leaves some information exposed for the mining tools...
... continuously during test processing and the examiner can not look at watch and equipments displaying parameter at the same time (2) Inconveniences in recording parameters and calculating results ... applications: confining stress or deviator stress and are generally classified as one of three conditions of drainage during application of the confining pressure and loading The three drainage conditions ... the confining stress and no excess pore pressures are developed during testing Consolidated drained tests are performed on all types of soil samples, including undisturbed, compacted and reconstituted...
... Describing Series Data Series data differs from the forms of data so far discussed mainly in the way in which the data enfolds the information The main difference is that the ordering of the data ... carries information This ordering, naturally, precludes random sampling since random sampling deliberately avoids, and actually destroys, any ordering Preserving the ordering is the main reason ... miner in preparing series data for modeling The miner also needs these same features when modeling This is not surprising, as finding the best way to expose the features of interest for modeling...
... subset of data points to reestimate the window’s central data point value Smoothing techniques include peak-valley-mean (PVM), median smoothing, and Hanning — Resmoothing is a smoothing technique ... frequencies, — Moving averages of various types A moving average involves using lagged values over the series data points and using all of the lagged values in some way to reestimate the data point value ... the data is a series It is not optimal because the ordering information is not fully used in the numeration However, using such information involves projecting the alpha values in a nonlinear...
... network uses the least during many training cycles 10.5.3 Estimating Variable Importance 3: Configuring and Training the Network Configuring the training parameters for assessing variable importance ... here.) Training the network requires presenting it with instances one after the other These instances, of course, comprise the miner-selected training data set For each instance of data presented, ... determines that training is complete As training begins, and the network better estimates the needed function in the training data set, the function improves its fit with the test data too When the...