fibonacci algorithm python

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Python implements the cache replacement algorithm with time for Space

Cache refers to a memory that can exchange high-speed data. It exchanges data with the CPU before the memory, so the speed is very fast. Cache is to temporarily store some data in some places, which may be memory or hard disk. The following describes how to implement the cache replacement algorithm for time-for-space in Python. For more information, see cache. cache refers to a memory that can exchange high

The basic algorithm of data regression classification prediction and Python implementation

the basic algorithm of data regression classification prediction and python ImplementAbout regression and classification of data and analysis of predictions. It is also considered as a relatively simple machine learning algorithm to discuss the algorithms for analyzing several comparative bases.A. KNN algorithmProximity algorithms, which can be used for regressi

--python realization of KNN classification algorithm

the sample set. In general, only the first K most similar data in a sample database is selected. Finally, select the most frequently occurring categories in the K most similar data. The algorithm is described as follows:1) Calculate the distance between the point in the data set of the known category and the current point;2) Sort by the increment order of distance;3) Select K points with the minimum distance from the current point;4) Determine the oc

--python realization of perceptual hashing algorithm

Recently, looking at the movement target tracking data, occasionally saw the zouxy09 god of a "based on the perceptual hashing algorithm visual tracking", it is very interesting. So I went to the relevant information of the perceptual hash, found that in the field of image search is very wide application, this technology I think a bit like template matching, the core is: through the similarity of fingerprints to search the most similar pictures. The C

Detailed explanation of Python algorithm application stack

. append (f (op1, op2) # put the calculation result into the stack and return stack. pop () # return the first element in the stack result = evalPostfix ('2 3 4 * + ') print (result) #14 Backpack problems Question There is a backpack that can hold 10kg of items, and now there are 6 items: Compile and find out all solutions that can fill your backpack, such as item 1 + Item 5. Solution code #! /Use/bin/env python # _ * _ coding: UTF-8 _ * _ def knapsa

Python Binary Search Algorithm instance

Python Binary Search Algorithm instance This example describes how to implement the Binary Search Algorithm in Python. Share it with you for your reference. The specific implementation method is as follows: ? 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 #! /Usr/bin/env

Implementation of KNN algorithm Python and simple digital recognition method

This paper describes the implementation of KNN algorithm Python and the method of simple digital recognition. Share to everyone for your reference. Specific as follows: KNN algorithm algorithm Advantages and disadvantages: Advantages: High accuracy, insensitive to outliers, no input data assumptionsCons: Both time com

Use only 30 lines of Python code to show the x algorithm

If you are interested in a logarithmic solution, you may have heard of accurate coverage. Given the set Y of a subset of complete x and X, there is a subset of Y y*, which makes y* a division of X. Here is an example of Python writing. X = {1, 2, 3, 4, 5, 6, 7}y = { ' A ': [1, 4, 7], ' B ': [1, 4], ' C ': [4, 5, 7], ' D ': [3, 5, 6], ' E ': [2, 3 , 6, 7], ' F ': [2, 7]} The only solution to this example is [' B ', ' D ', ' F ']. The exact cov

The interview is no longer scary, 20 lines of Python code to help you understand the LRU algorithm

LRU algorithm in the back-end engineer interview, is a more frequent topic, this article with everyone, understand the LRU algorithm, and finally with Python easy implementation of an LRU algorithm based on the cache.What is a cacheFirst look at a picture, when we visit the Web page, the browser will send a request to

Use only 30 lines of Python code to show the X algorithm _python

If you are interested in a logarithmic solution, you may have heard of accurate coverage. Given the set Y of a subset of complete x and X, there is a subset of Y y* that makes y* a partition of x. Here's an example of Python writing. X = {1, 2, 3, 4, 5, 6, 7} Y = { ' A ': [1, 4, 7], ' B ': [1, 4], ' C ': [4, 5, 7], ' D ': [3, 5, 6], ' E ': [2, 3, 6, 7], ' F ': [2, 7]} The only solution to this example is [' B ', ' D ', ' F '

Python multiple inheritance New algorithm C3 introduction _python

The MRO method is the resolution order, which is mainly used to determine the path (from which class) of the property on multiple inheritance. In the python2.2 version, the basic idea of the algorithm is to compile a list, including the searched class, based on the inheritance structure of each ancestor class, to delete duplicates by policy. However, in the maintenance of monotonicity has failed (sequential save), so from the 2.3 version, the use of

Python implementation of LRU algorithm

Lru:least recently used, the least recently used algorithm. Its use of the scene is: in a limited space to store objects, when the space is full, will be a certain principle to delete the original objects, commonly used principles (algorithms) have LRU,FIFO,LFU and so on. The algorithm is used in both the cache hardware of the computer and in the memory-to-virtual page replacement, and in the Redis cache sy

The mining of frequent itemsets implemented by fp-growth algorithm Python

This paper mainly introduces the algorithm of extracting frequent itemsets from Fp-tree.See MORE: Fp-growth algorithm introduction, fp_growth algorithm python implementation, fp-growth algorithm Python implementation of Fp-tree co

Python method for keyword matching using BF algorithm

In this paper, we describe the method of Python matching by BF algorithm. Share to everyone for your reference. The implementation method is as follows: The code is as follows: #!/usr/bin/python#-*-Coding:utf-8# filename BFImport time"""T= "A big apple,this is a big apple,this are a big apple,this is a Big Apple."p= "Apple""""T= "Why is it called a vector space

Python uses the BF algorithm to achieve keyword matching method _python

The example of this article is about Python using the BF algorithm to achieve keyword matching method. Share to everyone for your reference. The implementation methods are as follows: Copy Code code as follows: #!/usr/bin/python #-*-Coding:utf-8 # filename BF Import time """ T= "This are a big apple,this are a big apple,this are a big apple,this

2 ways to implement LRU algorithm in Python

This article mainly introduces Python to implement the LRU algorithm 2 kinds of methods, this paper gives the implementation of ordereddict, with dict+list implementation of two methods, the need for friends can refer to the Lru:least recently used, the least recently used algorithm. Its use of the scene is: in a limited space to store objects, when the space is

Binary search of Python algorithm

Description: Most of the code is found on the Internet, several code ideas summed upUsually write algorithm, used to write in C language, appear clear thinking. But suppose once the idea is determined, and do not want to make a draft. Want to write down at high speed to see the effect, or Python write faster. Also see personal hobbies. Internship with a colleague for Py

Binary search of Python algorithm

Description: Most of the code is found on the Internet, several code ideas summed upUsually write algorithm, used to write in C language, it seems clear thinking, but if once the idea is determined, and do not want to hit the draft, want to quickly write down to see the effect, or Python write faster, also see personal hobbies, internship when there is a colleague for P

The KNN algorithm implemented by Python

The KNN algorithm implemented by Python  Key words: KNN, K-Nearest neighbor (KNN) algorithm, Euclidean distance, Manhattan distanceKNN is classified by measuring the distance between different eigenvalues. The idea is that if a sample is the most similar in the K in the feature space (that is, the nearest neighbor in the feature space), the sample belongs to that

Apriori algorithm Python implementation

]) = =[]: num= Num+1C[i,-1] =Num Num=0returnCdefLimit (L):#Remove the C that does not meet the threshold valuerow = [] forIinchRange (L.shape[0]):ifL[I,-1] minsp:row.append (i) L=Np.delete (L, row, 0)returnLdefGenerate (L, K):#implementation of conversions from L to Cs = [] forIinchRange (L.shape[0]): S.append (List (l[i,:-1])) S_new= []#L = l.delete (L,-1, 1)#L = l.shape[1] forIinchRange (l.shape[0]-1): forJinchRange (i+1, L.shape[0]):if(l[j,-2]>l[i,-2]): t=list (np.copy (s[

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