ggplot plots

, self-help sampling, K-fold cross-validation and so on. Next you can use function Evalute () to evaluate the performance of multiple evaluation algorithms using the evaluation plan.2. Example AnalysisLibrary (Recommenderlab)Library (GGPLOT2)# #数据处理与数据探索性分析Data (Movielense)Image (Movielense)# get ratingsRatings.movie Summary (ratings.movie$ratings)# # Min. 1st Qu. Median Mean 3rd Qu. Max.# 1.00 3.00 4.00 3.53 4.00 5.00Ggplot (Ratings.movie, AES (x = ratings)) + Geom_histogram (fill = "Beige", co

Randnorm# #rnorm (3000) produces 3,000 positive too many distributions Randdensity# # # #dnorm (randnorm) to find its density function value Ggplot (Data.frame (x=randnorm,y=randdensity)) +aes (x=x,y=y) +geom_point () +labs (x= "Random Normal varables", y= " Randdensity ") # #将这个你太分分布数以及对应的密度函数值作为x, y-axis values, and draw point graphs P# #变量p作为该段代码的引用 Neg1seq# #生成一段序列, the starting value is min (randnorm), the end is to=-1, step 0.1 Lessthanneg1# #将序

Label:According to the characteristics of various industries, a variety of clustering algorithms are proposed, which are divided into several categories: hierarchy, Division, density, graph theory, grid and model. Among them, the density-based clustering algorithm is the most representative in Dbscan. Assuming a set of data, the R code of the generated data is as follows X1 0, Pi,length. out= -) Y10.1*rnorm ( -) X21.5+ SEQ (0, Pi,length. out= -) Y20.1*rnorm ( -) DataData.frame (C (X1,X2), C (y1

([ -1.12817385, 1.07053437, -65.81425599, -4.564575 , 6.17156198]), array([ 2.62704721e-01, 2.87680340e-01, 4.15643528e-70, 1.83764399e-05, 2.82461897e-08])) The first array is the t statistic, and the second array is the corresponding P value. Visualization Python has many visualization modules, and the most popular one is the matpalotlib library. We can also select the bokeh and seaborn modules. In my previous blog post, I have explained the function of the box map module in the matplotlib l

([2.62704721e-01, 2.87680340e-01, 4.15643528e-70, 1.83764399e-05, 2.82461897e-08])) The first array is the T statistic, and the second array is the corresponding P-value. Visualization of There are many visual modules in Python, the most popular being the Matpalotlib library. With a little mention, we can also choose the bokeh and Seaborn modules. In the previous blog post, I have explained the function of the box Whisker diagram module in the Matplotlib library. # Import the module for Plot

3.1 Basic Bar chartLibrary (GGPLOT2)Library (Gcookbook)Pg_mean #这是用到的数据Group weight1 Ctrl 5.0322 Trt1 4.6613 Trt2 5.526Ggplot (Pg_mean, AES (X=group, Y=weight)) + Geom_bar (stat= "Identity")The x-axis is a continuous variable or a factor, and the graph is different, and the group here is the factor.STR (Pg_mean)' Data.frame ': 3 obs. of 2 variables:$ group:factor W/3 Levels "Ctrl", "Trt1",..: 1 2 3 #可以看出group是因子$ weight:num 5.03 4.66 5.53Set the fill color with fill, set the border color with co

dataRanks Library (' TM ')Documents Row.names (documents) #获得语料库Corpus #R2版本用corpus Corpus #R2版本用corpus Corpus #去除英文停用词Corpus #得到词项文档矩阵DTM X Y Set.seed (1)Library (' Glmnet ')Performance For (Lambda in C (0.1, 0.25, 0.5, 1, 2, 5)){For (i-1:50){Indices Training.x Training.y Test.x Test.y Glm.fit Predicted.y Rmse Performance }}Ggplot (Performance, AES (x = Lambda, y = RMSE)) +stat_summary (fun.data = ' Mean_cl_boot ', Geom = ' errorbar ') +Stat_summary

The addition of p-value and significance markers in the R language Visual learning notesHttp://www.jianshu.com/p/b7274afff14f?from=timelineIn the previous article, I mentioned how to add the GGPUBR package to the ggplot diagram p-value and the significance of the markup, this article will be described in detail. Demo with Data set Toothgrowth#先加载包library(ggpubr)#加载数据集ToothGrowthdata("ToothGrowth")head(ToothGrowth)## len supp dose## 1 4.2 VC

= Fig.add_subplot (2,2,2) ax3 = Fig.add_subplot (2,1,2) Ax3.plot (Randn () cumsum (), ' k--') # Plt.plot (Randn () cumsum (), ' k--') equivalent ax1.hist (RANDN (+), bins = ten, color = ' B ', alpha = 0.3) #bins divided into how many intervals alpha transparency Ax2.scatter (Np.arange (+), Np.arange (+) + 3*RANDN (30)) 2.3 Creating a sub-graph mode twoFrom numpy.random import randn fig, axes = plt.subplots (2,2) #以数组方式访问 t = Np.arange (0., 5., 0.2)

(Array ([-1.12817385, 1.07053437,-65.81425599,-4.564575, 6.17156198]), array ([2.62704721e-01, 2.87680340e-01, 4.15643528e-70, 1.83764399e-05, 2.82461897e-08]) The first array is the T statistic, and the second array is the corresponding P value. Visualization of Python has many visual modules, the most popular of which is the Matpalotlib library. With a little mention, we can also select Bokeh and Seaborn modules. In the previous blog post, I have explained the Matplotlib library

: Color 1.1 r: Red 1.2 B: Blue 1.3 G: Green 1.3 y: Yellow 2. Data marker Markder 2.1 o: Circle 2.2. : Dot 2.2 D: Prism 3. Line LineStyle 3.1 without parameters is the default drawing point figure 3.2--: Dashed 3.3-: Solid line 4. Transparency Alpha 5. Size 6. Grid line Plt.grid (true,color= ' g ', linestyle= '-', linewidth= ' 2 ') # Region fill import Matplotlib.pyplot as Plt import numpy as NP X=np.linspace (0,5*np.pi,1000) Y1=np.sin (x) Y2=np.sin (2*x) plt.plot (x,y1) plt.plot (x,y2) # f

= pd.value_counts (pred_churn) # Calculate True Probabilities True_prob = {} for prob in Counts.index: true_prob[prob] = Np.mean (Is_churn[pred_churn = = Prob]) True_prob = PD. Series (True_prob) # pandas-fu counts = Pd.concat ([Counts,true_prob], Axis=1). Reset_index () Counts.columns = [' Pred_prob ', ' count ', ' true_prob '] counts Output results:We can see that a random forest predicts 75 people will have a 0.9 probability of loss, whereas in reality the group has about 0.97

providing support for data visualization on the Web. The charts it supports include bars, bars, lines, candlesticks, pie charts, radar, polar plots, scatter plots, burn charts, pyramid charts, and more. The Amcharts library is a completely separate class library that can be compiled and run directly without relying on any other third-party class libraries in your application. In addition to providing the m

symbols. As I said, it's basically safe, but ignoring it might get unwanted at some point like the example above. Another method was used to resolve the jpgraph. That is, you need to "new" an object by adding a so-called two-stage construct that can safely use the "Init ()" Method of the $this reference (simply because the $this reference in the constructor returns a copy of the object rather than as expected). So the above example would be implemented as follows: $myBattery = new Battery ()

First is not the source of the problem, ... My various sources of various updates, is definitely not the source of the problem.which I performedApt-get Install linux-headers-$ (uname-r)Prompt after this command:E: Unable to locate package Linux-headers-4.3.0-kali1-686-paeE: Unable to find any packages according to Glob ' Linux-headers-4.3.0-kali1-686-pae 'E: Unable to find any packages according to regular expression linux-headers-4.3.0-kali1-686-paeI searched for a moment: Apt-cache search Linu

ignoring it may at some point get unwanted effects like the example above. Another method was used in the jpgraph to solve the problem. That is, you need to "new" an object using the so-called two-phase construct by adding a safe use of the "Init ()" Method of the $this reference (simply because the $this reference in the constructor returns a copy of the object rather than is expected to do). So the example above will be implemented as follows: $myBattery = new Battery (); $myDisplay = new D

Note: Import Pyplot as PLT can also Two types of common graphs Line and scatter plots (using the plot () command), histogram (using the hist () command) 10 percent Line charts Scatter chart lines and scatter plots Line Chart line plots (lines associated with a set of x and Y values) Import NumPy as NP Import Pylab as Pl x = [1, 2, 3, 4, 5]# make an ar

supports different curves with different styles and colors to display. In the following code, the plot method has 3 parameters for a group of 3 groups, and the parameters for each group are x-axis, y-coordinate, and style. Style usage: Format: ' [Color][marker][line] ' The first letter of the style represents the color, and the supported colors are: R (Red), g (green), B (blue), C (cyan), M (Megenta), Y (Yellow), W (White), K (black). The second part of the style represents the fill symbol for

OPENCV InformationImage Processing Class Library cimgThe CIMG library is a powerful database of image processing classes. Use this class in code to import/export, process, and display pictures, which is a powerful C + + toolbox for processing images.2D Graphics Library aggAGG, full name: Anti-graingeometry, is an open source, efficient 2D graphics library. The functionality of Agg is very similar to GDI + 's, but provides a more flexible programming interface than GDI +, which produces a very h

Today, the second part of script design is the development of war games. In war games, I especially love the glorious legend of heroes and the legend of Cao. My Three Kingdoms of multi-platform games were also developed based on the legend of the Three Kingdoms. This is no exception. It is developed based on the transplantation of Cao Zhuan and then extended to develop the game. Friends familiar with CaO Zhuan know that Cao Zhuan is divided into R plots