[SOLVED] CS代考 AugustReferralExercise 01

AugustReferralExercise 01

AugustReferralExercise 01
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Table of Contents
0. Setup the document1
1. Read and Investigate the Data1
2. Cluster Recipes2
3. Investigate Clusters2
4. Conclusion3

0. Setup the document
Clear the workspace
Load all the packages you need for this notebook here.
1. Read and Investigate the Data
Read in the data.
recipes <- read_csv(‘./recipes.csv’)## — Column specification ——————————————————–## recipe_id = col_double(),## ingredient = col_character(),## cuisine = col_character()Make sure the ID variable is a character or factor, not numeric.# your code hereWhat variables are in the dataset? What data type are they?# your code hereHow many different unique ingredients are there?# your code hereWhat are the top five most frequent ingredients?# your code hereCreate a frequency bar chart of the ingredients showing the distribution of ingredients.# your code hereOptional: Create a dot plot of the top 5% of ingredients.# your code here2. Cluster RecipesUses this Jaccard similarity function to compare two sets of ingredients for a pair of recipes.source(‘jaccard_matrix.R’)# your code hereUse kmeans to cluster the recipes. First determine the appropriate number of centroids to use. Compute the total within sum of squares using between one and twenty clusters. Then plot the results. Use the elbow method to determine number of clusters.# your code hereUse your chosen number of clusters to cluster the recipes. Use a high nstart to ensure a good quality solution.# your code hereUse fviz_cluster to visualize the clusters. What patterns do you see?# your code here3. Investigate ClustersMerge the clusters back into the recipe dataset so that each recipe has a new variable with the cluster ID.# your code hereWhat are the top 5 ingredients and cuisines in each cluster?# your code here# your code here4. ConclusionWhat patterns did the cluster analysis and PCA from fviz_cluster reveal?What further cleaning or processing of the data do you think is necessary?What other visualizations or analyses could you perform explain the patterns that you see in the data?程序代写 CS代考加微信: assignmentchef QQ: 1823890830 Email: [email protected]