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- # define stemmer functionstemmer = SnowballStemmer('english') # tokenise datatokeniser = TreebankWordTokenizer()tokens = tokeniser.tokenize(data) # define lemmatiserlemmatizer = WordNetLemmatizer() # bag of wordsdef bag_of_words_count(words, word_dict={}): """ this function takes in a list of words and returns a dictionary with each word as a key, and the value represents the number of times that word appeared""" for word in words: if word in word_dict.keys(): word_dict[word] += 1 else: word_dict[word] = 1 return word_dict # remove stopwordstokens_less_stopwords = [word for word in tokens if word not in stopwords.words('english')] # create bag of wordsbag_of_words = bag_of_words_count(tokens_less_stopwords) Use the stemmer and lemmatizer functions (defined in the cells above) from the relevant library to find the stem and lemma of the nth word in the token list. Function Specifications: Should take a list as input and…don't use others answer, show your work step by stepFIX THIS CODE Using python Application CODE: import csv playersList = [] with open('Players.csv') as f: rows = csv.DictReader(f) for r in rows: playersList.append(r) teamsList = [] with open('Teams.csv') as f: rows = csv.DictReader(f) for r in rows: teamsList.append(r) plays=len(playersList) for i in range(plays): if playersList[i]['team']=='Argentina' and int(playerlist[i]['minutes played'])<200 and int(playersList[i] ['shots'])>20: print(playersList[i]['last name']) c0=0 c1=0 c2=0 for i in range(len(teamsList)): if int(teamsList[i]['redCards'])==0: c0=c0+1 if int(teamsList[i]['redCards'])==1: c1=c1+1 if int(teamsList[i]['redCards'])==2: c2=c2+1 print("Number of teams with zero redcards:",c0) print("Number of teams with zero redcards:",c1) print("Number of teams with zero redcards:",c2) ratio=0 for i in range(len(teamsList)): if int(teamsList[i]['games']>3) and if int(teamsList[i]['goalsFor'])/int(teamsList[i]['goalsAgainst'])<ratio:…
- So I have this artificial intelligence assignment and I’m struggling with the search methods implementations it would be nice if I can get the code in Java or at least a pseudocode for their implementationstext file 80 1 2 3 100 100 100 1001 0 2 100 3 4 100 1002 2 0 4 4 100 5 1003 100 4 0 100 100 4 100100 3 4 100 0 3 3 3100 4 100 100 3 0 100 1100 100 5 4 3 100 0 2100 100 100 100 3 1 2 0 My code below. I am getting an error when trying to create my adjacency matrix. i dont know what i am doing wrong def readMatrix(inputfilename): ''' Returns a two-dimentional array created from the data in the given file. Pre: 'inputfilename' is the name of a text file whose first row contains the number of vertices in a graph and whose subsequent rows contain the rows of the adjacency matrix of the graph. ''' # Open the file f = open(inputfilename, 'r') # Read the number of vertices from the first line of the file n = int(f.readline().strip()) # Read the rest of the file stripping off the newline characters and splitting it into # a list of intger values rest = f.read().strip().split() # Create the adjacency matrix adjMat = []…THIS IS MY CODE HELP ME ACHIEVE POINTS OUTLINED BELOW : #include <stdio.h>#include <stdlib.h>#include <string.h>#include <float.h>#include "graph.h"#include "dijkstra.h" #define INFINITY DBL_MAX /* find shortest paths between source node id and all other nodes in graph. *//* upon success, returns an array containing a table of shortest paths. *//* return NULL if *graph is uninitialised or an error occurs. *//* each entry of the table array should be a Path *//* structure containing the path information for the shortest path between *//* the source node and every node in the graph. If no path exists to a *//* particular desination node, then next should be set to -1 and weight *//* to DBL_MAX in the Path structure for this node */Path *dijkstra(Graph *graph, int id, int *pnEntries){ int n; int i, j; int* nv = get_vertices(graph, &n); int *S = malloc(n * sizeof(int)); double *D = malloc(n * sizeof(double)); int *R = malloc(n…
- import numpy as np%matplotlib inlinefrom matplotlib import pyplot as pltimport mathfrom math import exp np.random.seed(9999)def is_good_peak(mu, min_dist=0.8): if mu is None: return False smu = np.sort(mu) if smu[0] < 0.5: return False if smu[-1] > 2.5: return False for p, n in zip(smu, smu[1:]): #print(abs(p-n)) if abs(p-n) < min_dist: return False return True maxx = 3ndata = 500nset = 10l = []answers = []for iset in range(1, nset): npeak = np.random.randint(2,4) xs = np.linspace(0,maxx,ndata) ys = np.zeros(ndata) mu = None while not is_good_peak(mu): mu = np.random.random(npeak)*maxx for ipeak in range(npeak): m = mu[ipeak] sigma = np.random.random()*0.3 + 0.2 height = np.random.random()*0.5 + 1 ys += height*np.exp(-(xs-m)**2/sigma**2) ys += np.random.randn(ndata)*0.07 l.append(ys) answers.append(mu) p6_ys = lp6_xs =…Let U = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}; M = {3, 5, 7, 9, 10}; N = {3, 4, 9, 10}; and O = {6, 7,8, 9, 10}. List the members of the indicated set, using set braces:(i) (N nO)'(ii) M u (N - O)(iii) MΔO(iv) M n N’nO@return index of the point that is closest to the origin, which is (0, 0) * In case of a tie, return the lowest index */ public int closestToOriginIndex() { return 0; }
- Body of the Loop: A reasonable step would be: Choose some nodeu from foundNotHandled, and handle it. This involves following all the edges from u. Newly found nodes are now added to the set foundNotHandled (if they have notbeen found already). u is moved from foundNotHandled to foundHandled.PYTHON: Code a traversal in python. The expected output is in the image below.Any time you design code with an artificial limit someonewill exceed it. For example, consider the code:void err(const char* const fmt, int a = 0, int b = 0, int c = 0, int d = 0, int e = 0){ fprintf(stderr, "Fatal Error:\n"); fprintf(stderr, fmt, a, b, c, d, e); fprintf(stderr, "\n"); abort();}Now this works if you wish to write simple messages:err(“Size parameter (%d) out of range”, size);But what happens when we wish to a slightly more complex call?err(“Point (%d,%d) outside of box (%d,%d), (%d,%d)”, point.x, point.y, box.x1, box.y1, box.x2, box.y2);Our function can take a format and up to five parameters. We just gave itsix. It's not going to work.Now we could fix the err function to add another parameter, but thatwould only work until we needed seven parameter. Another change would beneeded at eight and so on.
