weka

问题 I tried to add weka with android but got these errors. I should say that when I run the class that contain all my weka code it runs perfectly but when I call this class using one of the activity I get the errors. Invoke-customs are only supported starting with Android O (--min-api 26) Message{kind=ERROR, text=Invoke-customs are only supported starting with Android O (--min-api 26), sources=[Unknown source file], tool name=Optional.of(D8)} I looked for a solution i found that you have to put

问题 Overview I am using the WEKA API 3.7.10 (developer version) to use my pre-made .model files. I made 25 models: five outcome variables for five algorithms. J48 decision tree. Alternating decision tree Random forest LogitBoost Random subspace I am having problems with J48, Random subspace and random forest. Necessary files The following is the ARFF representation of my data after creation: @relation WekaData @attribute ageDiagNum numeric @attribute raceGroup {Black,Other,Unknown,White}

问题 I want to connect to MSSQL server in Weka 3.8 . I tried lots of things and I couldn't find a way to connect to SQLServer 2012 Database . Error: driver not found. I applied all steps about JDBC-ODBC bridge (link below) https://andersspur.wordpress.com/2013/10/11/connect-weka-to-sql-server-2012-and-14/ ErrorImage : 回答1: I know it is late, but I had the same problem, and this took me a while to find the solution. I am almost sure you found the solution. In here, it is the second step. However, I

问题 I am using Weka for clustering some data and was running into a very odd problem. When I use the normal "Cluster" Tool on a data set, I am getting a result of Cluster 1: 87 instances Cluster 2: 88 instances Cluster 3: 181 instances This is what I sort of expected from the data I had, so I consider this a good result. However, I want to add this cluster as a class and save it as a new .arff file, so I am trying to use the "Add Cluster" filter that Weka provides. Now, in this filter, I select

问题 After getting very excited by what seemed like excellent results from using the MLP within the Weka GUI on my pricing data, I've coded up a bit of Java that uses an MLP with the same parameters. Here is where the fun starts, the results are completely different, I've now found that this appears to be be due to rounding differences. The GUI rounds to 3 dp, my java code rounds to 5 dp. I've looked through the manuals but I can't seem to find an option to force the GUI to use 5dp precision on

问题 I have data as follows in order to do a predictive learning as to what feature do people find attractive in a model when purchasing clothes online. So I have data as follows. COLORofCLOTHING MODELHAIR_COLOR MODEL_BUILD SELLER_CATEGORY Red Black Lean 1 Blue Brown Lean 5 Black Blonde Healthy 10 In order to predict if the clothing will sell well given a set of attributes. However seller category can be anything between 1 to 10 (1 being best and 10 being worst) I am not sure how to approach this

问题 I'm new to Weka and having problems converting a CSV file containing Tweets into an Arff file. The CSV looks like this Tweet,Class Conference Update: 50% Off Registration to End .. http://t.co/nZtkSzZnJ6,Yes When I try to convert to .arff using Explorer, I receive the following error "...not recognized as an CSV data files Reason: wrong number of values. Read 1 expected 2, read token[EOF], line 2" Removing the "%" character allows the file to convert to arff without error. I could remove "%"

问题 I'm trying to classify an unlabelled string using Weka, I'm not an expert in data mining so i have been struggling with the different terms. What I'm doing is I am providing the training data and setting the unlabeled string after running the M5Rules classifier, I'm actually getting an output but i have no idea what it mean: run: {17 1,35 1,64 1,135 1,205 1,214 1,215 1,284 1,288 1,309 1,343 1,461 1,493 1,500 1,552 1,806 -0.038168} | -0.03816793850062397 -0.03816793850062397 -> Results ======

问题 I am new to Weka. I am trying to run WEKA using API's and have found out that the results from the WEKA GUI does not match to the one produced by the Java code. I am trying to run a RandomForest Algorithm by providing TrainingSet and Test Set. Here is the code snippet: DataSource ds = new DataSource(trainingFile); Instances insts = ds.getDataSet(); insts.setClassIndex(insts.numAttributes() - 1); Classifier cl = new RandomForest(); RandomForest rf = (RandomForest)cl; // rf.setOptions(options);

问题 Apologies as I'm a complete novice when it comes to Weka. I have 100 instances and each instance has 400 attributes most of which have a single value. However some attributes have multiple values as they contain a time component. I was wondering if Weka can analyse multiple values for one attribute and if so, how do I separate these values so that weka can read them (e.g. commas, semi-colons?) Many Thanks for your help R 回答1: Weka natively works with a format called arff acronym for Attribute