Where communities thrive


  • Join over 1.5M+ people
  • Join over 100K+ communities
  • Free without limits
  • Create your own community
People
Repo info
Activity
    lesshaste
    @lesshaste
    but it looks like it should be fixed in rhiever/tpot#284
    was that never merged?
    Dmitry Mottl
    @Mottl
    Hi, everybody! Could someone help me with a xgboost parameters. I have the following code:
    xgb = XGBRegressor(n_estimators=1000, silent=0)
    xgb.fit(train.as_matrix(), trainY, verbose=1, eval_metric="rmse")
    P = xgb.predict(test.as_matrix())
    it doesn't output RMSE metric during training. Where am I wrong?
    Ketan Kunde
    @KetanKunde_twitter
    Hi
    i was looking to build xgboost from source
    just wanted to know if anyone on the group has tried doing it before?
    Ketan Kunde
    @KetanKunde_twitter
    also just wanted to confirm whether this is 100% open source
    Guryanov Alexey
    @Goorman
    Hello. Does anyone know if i can slice xgboost's DMatrix by column or block certain features from being used in specific train instance?
    Chris Chow
    @ckchow
    @Goorman it's probably easier to make a new DMatrix with those rows removed or censored in whatever way you need.
    lesshaste
    @lesshaste
    how can you use the pearson correlation coefficient as the loss function with the xgboost regressor?
    Guryanov Alexey
    @Goorman
    @ckchow you have probably meant columns removed and yes this is the only solution i see right now. The problem is that i have to construct DMatrix from sparse libsvm file, and for example to perform greedy feature selection i would have to create new (big) libsvm file every iteration. Which is annoying.
    Chris Chow
    @ckchow
    Oh, I see. can't you construct DMatrices in memory from arrays of arrays?
    Chris Chow
    @ckchow
    At least in Java there is a float[][] constructor, and I think there's a numpy constructor in python as well. might be out of luck if you're using the command line version.
    lesshaste
    @lesshaste
    hi... does anyone understand why xgboost is so slow if you have lots of classes? This code shows the problem https://bpaste.net/show/f7573b5a2fb9 RandomForestClassifier takes about 15 seconds
    but xgboost never terminates at all for me
    Lyndon White
    @oxinabox
    I am training a binary classifier.
    In the problem I am working on,
    I can generate more training data at will.
    In that by running a simulation I can (determenistically) determine the correct label for any feature set
    Each training case takes a bit to generate (say 0.5 seconds).
    The main motivation for training a classifier is that evaluating via simulation takes too long.
    Is there a specific way to task advantage of my capacity to generate more data, that I can do in xgboosting,
    that I couldn't do with say a SVM?
    Its almost an Active Learning problem
    Lyndon White
    @oxinabox
    I'm not sure if there is anything beyond: "Generate more data, both for training and validation , until the validation error hits 0"
    KOLANICH
    @KOLANICH
    Hi everyone! Could anyone explain what are the arguments of a custom loss function?
    objective function
    Data Scientist
    @JayKimBravekjh
    Hi everyone. I joined this room first time today, nice to meet you all
    Asbjørn Nilsen Riseth
    @anriseth
    Is there a built-in way to run XGBoost with a weighted mean square loss function?
    Something like i=1Dwi(yiy^i)2 \sum_{i=1}^D w_i(y_i-\hat{y}_i)^2
    binyata
    @binyata
    is there a general reason why xgboost predict returns only nan?
    this is for python
    xiaolangyuxin
    @xiaolangyuxin
    multithread
    xgboost predict for multithread works bad
    on windows xp,i found a lots of issues for xgboost,exspacially,
    uaing
    using lolibray
    Peter M. Landwehr
    @pmlandwehr
    Anybody have a changelog for 0.7.post4?
    AbdealiJK
    @AbdealiJK
    Rydez
    @Rydez
    For XGBoost, when considering time series data, is it worth creating features which represent a change in other features? For example, say I have the feature "total_active_users". Would it make sense to have a feature "change_in_total_active_users"? Or, would that just be redundant?
    Harshal
    @geekyharshal
    Hello people
    Can someone suggest how to begj with xgboost ?
    Harshal
    @geekyharshal
    begin*
    Tommy Yang
    @joyang1
    I use xgboost4j-0.80.jar predictleaf always return 3 leafindex for one label? is this any error?
    @all
    @/all
    Tommy Yang
    @joyang1
    have anyone can answer me?
    Tommy Yang
    @joyang1
    :joy: :joy_cat: :joy:
    Tommy Yang
    @joyang1
    :joy:
    Tommy Yang
    @joyang1
    I used xgboost4j-0.80.jar, xgboost train parameter of round is 800 and train data is 2000000. When I use predictleaf to get leafIndex, the jvm crashed.

    #

    A fatal error has been detected by the Java Runtime Environment:

    #

    SIGSEGV (0xb) at pc=0x00007f42160bf902, pid=880, tid=0x00007f42175f2700

    #

    JRE version: Java(TM) SE Runtime Environment (8.0_171-b11) (build 1.8.0_171-b11)

    Java VM: Java HotSpot(TM) 64-Bit Server VM (25.171-b11 mixed mode linux-amd64 compressed oops)

    Problematic frame:

    V [libjvm.so+0x6d6902] jni_SetFloatArrayRegion+0xc2

    #

    Core dump written. Default location: /data/suzhe/suzhe-1.0-SNAPSHOT/core or core.880

    #

    If you would like to submit a bug report, please visit:

    http://bugreport.java.com/bugreport/crash.jsp

    #

    Java frames: (J=compiled Java code, j=interpreted, Vv=VM code)
    j ml.dmlc.xgboost4j.java.XGBoostJNI.XGBoosterPredict(JJII[[F)I+0
    j ml.dmlc.xgboost4j.java.Booster.predict(Lml/dmlc/xgboost4j/java/DMatrix;ZIZZ)[[F+45
    j ml.dmlc.xgboost4j.java.Booster.predictLeaf(Lml/dmlc/xgboost4j/java/DMatrix;I)[[F+6
    j com.jianshu.suzhe.LRTrainer.train()V+23
    j com.jianshu.suzhe.LRTrainer.main([Ljava/lang/String;)V+30
    v ~StubRoutines::call_stub
    Stack: [0x00007f42174f2000,0x00007f42175f3000], sp=0x00007f42175f1590, free space=1021k
    Native frames: (J=compiled Java code, j=interpreted, Vv=VM code, C=native code)
    V [libjvm.so+0x6d6902] jni_SetFloatArrayRegion+0xc2
    C [libxgboost4j8098523902211486429.so+0x9001c] Java_ml_dmlc_xgboost4j_java_XGBoostJNI_XGBoosterPredict+0x5c
    Can someone suggest how to solve this problem?
    thx~~~