silhouette | 易学教程

Silhouette plot is not working for more than 200 rows of data

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问题 I am trying to plot the silhouette for my k-means, using shiny. Below is the piece of code: dissE <- daisy(pima_diabetes_kmean[, c(input$models_to_consider)]) dE2 <- dissE ^ 2 sk2 <- silhouette(k.means.fit.knn()$cl, dE2) plot(sk2) It results in the following plot, where clusters are missing: However, if I change the code to use only 200 rows of data (or use window() ), it does work. But I do not want my results in a separate window, as I am using shiny. I want the results to be on the same

Silhouette plot is not working for more than 200 rows of data

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How can I change the color to a variable other than cluster number in fviz_silhouette

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来源： https://stackoverflow.com/questions/61820019/how-can-i-change-the-color-to-a-variable-other-than-cluster-number-in-fviz-silho

Play 2.5 with Silhouette 4.0 - Credential Provider

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问题 I am trying to write a sample app with Play 2.5 using Silhouette 4.0 for user/password authentication. Source code available at : https://github.com/pariksheet/dribble I am stuck at setting requestProvider in Environment object Environment[JWTEnv]( identityService, authenticatorService, Seq(), eventBus ) As I am not able to figure out the solution, I am injecting Credential Provider in my all controller classes. class MyController @Inject() (val messagesApi: MessagesApi,val silhouette:

Play 2.5 with Silhouette 4.0 - Credential Provider

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unable to create `Environment` in `Silhouette`

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问题 I am trying to create the Environment in Silhouette but am unable to. I have defined the Identity and Authenticator as follows trait SessionEnv extends Env { type I = User type A = SessionAuthenticator } Next, I suppose I have to create the Environment . For that I have written the following code but am stick as I do not understand how to pass the different parameters expected by Environment 's apply method Environment companion object's apply method has signature def apply[E <: Env](

How to use silhouette score in k-means clustering from sklearn library?

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问题 I'd like to use silhouette score in my script, to automatically compute number of clusters in k-means clustering from sklearn. import numpy as np import pandas as pd import csv from sklearn.cluster import KMeans from sklearn.metrics import silhouette_score filename = "CSV_BIG.csv" # Read the CSV file with the Pandas lib. path_dir = ".\\" dataframe = pd.read_csv(path_dir + filename, encoding = "utf-8", sep = ';' ) # "ISO-8859-1") df = dataframe.copy(deep=True) #Use silhouette score range_n

How to use silhouette score in k-means clustering from sklearn library?

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I'd like to use silhouette score in my script, to automatically compute number of clusters in k-means clustering from sklearn. import numpy as np import pandas as pd import csv from sklearn.cluster import KMeans from sklearn.metrics import silhouette_score filename = "CSV_BIG.csv" # Read the CSV file with the Pandas lib. path_dir = ".\\" dataframe = pd.read_csv(path_dir + filename, encoding = "utf-8", sep = ';' ) # "ISO-8859-1") df = dataframe.copy(deep=True) #Use silhouette score range_n_clusters = list (range(2,10)) print ("Number of clusters from 2 to 9: \n", range_n_clusters) for n