1、In this view, WEKA allows you to review the data you're working with.
在這個視圖中，WEKA允許您查閱正在處理的數(shù)據(jù)。

2、After selecting the file, your WEKA Explorer should look similar to the screenshot in Figure 3.
在選擇了文件后，WEKAExplorer應(yīng)該類似于圖3中所示的這個屏幕快照。

3、Load the data file bmw-training.arff into WEKA using the same steps we've used up to this point.
使用我們之前使用過的相同步驟來將數(shù)據(jù)文件bmw - training . arff(參見下載)載入WEKA。

4、Yet, the results we get from WEKA indicate that we were wrong.
然而，我們從WEKA 獲得的結(jié)果表明我們錯了。

5、So let's see how to get our data into a format that the WEKA API can use.
那么讓我們看看如何將我們的數(shù)據(jù)轉(zhuǎn)換成weka API可以使用的格式。

6、NOTE: I would warn you ahead of time that the WEKA API can be difficult to navigate at times.
注：我最好提前告誡您WEKAAPI有時很難導航。

7、As you can imagine, the central building block in the WEKA API is going to be the data.
正如您所想，WEKAAPI內(nèi)的這個中心構(gòu)建塊就是數(shù)據(jù)。

8、WEKA is powerful and 100-percent free to use.
WEKA功能強大且100 %免費。

9、This tells WEKA that we want to build a regression model.
這會告訴WEKA我們想要構(gòu)建一個回歸模型。

weka翻譯