iterative process
description: numerical method in which the n-th approximation of the solution is obtained on the basis on the (n-1) previous approximations
212 results
The Radical Fund: How a Band of Visionaries and a Million Dollars Upended America
by John Fabian Witt · 14 Oct 2025 · 735pp · 279,360 words
difficulty was that the bureaucracy that industrial democracy required was not costless. It risked sapping the collective energies that maintained workers’ power. For Hillman, an iterative process of learning—in his socialist youth he would have called it dialectical—offered a basis for achieving democratic control of industry while maintaining class solidarity
Our Dollar, Your Problem: An Insider’s View of Seven Turbulent Decades of Global Finance, and the Road Ahead
by Kenneth Rogoff · 27 Feb 2025 · 330pp · 127,791 words
, prices move to bring demand and supply in line; in the old Soviet Union, almost everything was done by command and control. It was an iterative process whereby the central government planners would allocate inputs across firms and industries, generally starting with what had been needed the previous year. The Kremlin planners
vN: The First Machine Dynasty (The Machine Dynasty Book 1)
by Madeline Ashby · 28 Jul 2012 · 343pp · 93,544 words
finished the first year of my second Master's – a design degree in strategic foresight. So I had spent months listening to discussions about the iterative process. And I started to realize that a self-replicating species of machine wouldn't have the usual fears about its offspring repeating its signature mistakes
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. Normally he gives me the end of all my stories, and this time he helped me see a new beginning. In short: it was an iterative process. ANGRY ROBOT A member of the Osprey Group Lace Market House, 54-56 High Pavement, Nottingham, NG1 1HW, UK www.angryrobotbooks.com No three rules
The C++ Programming Language
by Bjarne Stroustrup · 2 Jan 1986 · 923pp · 516,602 words
those individual pieces of code. A design is the end product of the design process (as far as there is an end product of an iterative process). It is the focus of the communication between the designer and the programmer and between programmers. It is important to have a sense of proportion
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interfaces. – Separate functions into public and protected operations. – Specify the exact type of the operations on the classes. Note that these are steps in an iterative process. Typically, several loops through this sequence are needed to produce a design one can comfortably use for an initial implementation or a reimplementation. One advantage
The Art of Computer Programming
by Donald Ervin Knuth · 15 Jan 2001
, with running time approximately the same as that of Algorithms L and T. Iteration of series. If we want to study the behavior of an iterative process xn «— f(xn-i), we are interested in studying the n-fold composition of a given function / with itself, namely xn = /(/(... f{xo) •••))• Let us
Python Cookbook
by David Beazley and Brian K. Jones · 9 May 2013 · 1,606pp · 168,061 words
re >>> re.sub('\s+', ' ', s) 'hello world' >>> It is often the case that you want to combine string stripping operations with some other kind of iterative processing, such as reading lines of data from a file. If so, this is one area where a generator expression can be useful. For example: with
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input sequences have been fully consumed. 4.16. Replacing Infinite while Loops with an Iterator Problem You have code that uses a while loop to iteratively process data because it involves a function or some kind of unusual test condition that doesn’t fall into the usual iteration pattern. Solution A somewhat
Clean Agile: Back to Basics
by Robert C. Martin · 13 Oct 2019 · 333pp · 64,581 words
loops. Both want to deliver high-quality, valuable work, and both want professionalism. In order to achieve business agility, companies need not only collaborative and iterative processes, but also good engineering skills. Combining Agile and Craftsmanship is the perfect way to achieve that. Conclusion At the Snowbird meeting in 2001, Kent Beck
Text Analytics With Python: A Practical Real-World Approach to Gaining Actionable Insights From Your Data
by Dipanjan Sarkar · 1 Dec 2016
the algorithm for everyone's benefit: Initialize the necessary parameters. For each document, randomly initialize each word to one of the K topics. Start an iterative process as follows and repeat it several times. For each document D: For each word W in document: For each topic T: Compute , which is proportion
Data Mining: Concepts, Models, Methods, and Algorithms
by Mehmed Kantardzić · 2 Jan 2003 · 721pp · 197,134 words
. The entire process of applying a computer-based methodology, including new techniques, for discovering knowledge from data is called data mining. Data mining is an iterative process within which progress is defined by discovery, through either automatic or manual methods. Data mining is most useful in an exploratory analysis scenario in which
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, system identification is not a one-pass process: Both structure and parameter identification need to be done repeatedly until a satisfactory model is found. This iterative process is represented graphically in Figure 1.1. Typical steps in every iteration are as follows: 1. Specify and parameterize a class of formalized (mathematical) models
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sufficiently precisely that a single and simple application of the method will suffice. In fact, what happens in practice is that data mining becomes an iterative process. One studies the data, examines it using some analytic technique, decides to look at it another way, perhaps modifying it, and then goes back to
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will be applied in one iteration only for two adjacent intervals with a minimum χ2 and, at the same time, with χ2 < threshold value. The iterative process will continue with the next two adjacent intervals that have the minimum χ2. We will just show one additional step, somewhere in the middle of
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of the samples may be selected more than once. Random sampling is not a one-time activity in a data-mining process. It is an iterative process, resulting in several randomly selected subsets of samples. The two basic forms of a random sampling process are as follows. 1. Incremental Sampling. Mining incrementally
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of the network. Neuron k is driven by input vector X(n), where n denotes discrete time, or, more precisely, the time step of the iterative process involved in adjusting the input weights wki. Every data sample for ANN training (learning) consists of the input vector X(n) and the corresponding output
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will continue either by using new training samples or by using the same data samples in the next iterations. As to when to finish the iterative process is defined by a special parameter or set of parameters called stopping criteria. A learning algorithm may have different stopping criteria, such as the maximum
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’s node weight vector and the current input sample, making the node closer to be “representative” for the sample. The SOM learning procedure is an iterative process that finds the parameters of the network (weights w) in order to organize the data into clusters that keep the topological structure. Thus, the algorithm
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phase; (b1) count phase; (b2) select phase In our example, because there is no candidate 4-itemset to be constituted from L3, Apriori ends the iterative process. Apriori counts not only the support of all frequent itemsets, but also the support of those infrequent candidate itemsets that could not be eliminated during
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that this section only gives a general description of the basics of GAs. Detailed implementations of GAs vary considerably, but the main phases and the iterative process remain. At the end of this section we can summarize that the major components of GA include encoding schemata, fitness evaluation, parent selection, and application
Gnuplot in Action: Understanding Data With Graphs
by Philipp Janert · 2 Jan 2010 · 398pp · 31,161 words
workflow of all work with gnuplot: plot, examine, repeat—until you have found out whatever you wanted to learn from the data. Gnuplot supports the iterative process model required for exploratory work perfectly. 1.3.1 Gnuplot isn’t GNU To dispel one common confusion right away: gnuplot isn’t GNU software
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. You may also want to take a look at the gnuplot reference documention for further discussion and additional features. Since the fitting algorithm is an iterative process, it’s not guaranteed to converge. If the iteration doesn’t converge, or converges to an obviously wrong solution, try to initialize the fitting parameters
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