Upload blackbox yahpo-iaml_glmnet

yahpo/iaml_glmnet/best_params_resnet.json

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+{"d": 128, "d_hidden_factor": 1.0503156355832801, "hidden_dropout": 0.03915074913174817, "lr": 0.008140322329476278, "mixup": true, "n_layers": 2, "opt_tfms_alpha": false, "opt_tfms_auc": true, "opt_tfms_f1": false, "opt_tfms_ias": true, "opt_tfms_logloss": true, "opt_tfms_mec": false, "opt_tfms_mmce": false, "opt_tfms_rammodel": true, "opt_tfms_rampredict": false, "opt_tfms_ramtrain": false, "opt_tfms_s": true, "opt_tfms_timepredict": false, "opt_tfms_timetrain": true, "opt_tfms_trainsize": true, "tfms_auc": "tlog", "tfms_ias": "tlog", "tfms_logloss": "tlog", "tfms_rammodel": "tnexp", "tfms_s": "tlog", "tfms_timetrain": "tlog", "tfms_trainsize": "tlog", "use_residual_dropout": false}

yahpo/iaml_glmnet/config_space.json

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+{
+  "hyperparameters": [
+    {
+      "name": "alpha",
+      "type": "uniform_float",
+      "log": false,
+      "lower": 0.0,
+      "upper": 1.0,
+      "default": 0.5
+    },
+    {
+      "name": "s",
+      "type": "uniform_float",
+      "log": true,
+      "lower": 0.00010000000000000009,
+      "upper": 999.9999999999998,
+      "default": 0.316227766
+    },
+    {
+      "name": "task_id",
+      "type": "categorical",
+      "choices": [
+        "40981",
+        "41146",
+        "1489",
+        "1067"
+      ],
+      "default": "40981",
+      "probabilities": null
+    },
+    {
+      "name": "trainsize",
+      "type": "uniform_float",
+      "log": false,
+      "lower": 0.03,
+      "upper": 1.0,
+      "default": 0.525
+    }
+  ],
+  "conditions": [],
+  "forbiddens": [],
+  "python_module_version": "0.4.19",
+  "json_format_version": 0.2
+}

yahpo/iaml_glmnet/encoding.json

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+{"task_id": {"#na#": 0, "1067": 1, "1489": 2, "40981": 3, "41146": 4}}

yahpo/iaml_glmnet/metadata.json

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+{"metric_elapsed_time": "time", "metric_default": "val_accuracy", "resource_attr": "st_worker_iter"}

yahpo/iaml_glmnet/model.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5c9b1541e37604993098ba23b04695bfe38d009108e9de0a26c3f161265b5a7a
+size 867133

yahpo/iaml_glmnet/param_set.R

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+search_space = ps(
+  alpha = p_dbl(lower = 0, upper = 1),
+  s = p_dbl(lower = log(1e-4), upper = log(1000), tags = "log", trafo = function(x) exp(x)),
+  trainsize = p_dbl(lower = 0.03, upper = 1, tags = "budget"),
+  task_id = p_fct(levels = c("40981", "41146", "1489", "1067"), tags = "task_id")
+)
+
+domain = ps(
+  alpha = p_dbl(lower = 0, upper = 1),
+  s = p_dbl(lower = 1e-4, upper = 1000),
+  trainsize = p_dbl(lower = 0.03, upper = 1, tags = "budget"),
+  task_id = p_fct(levels = c("40981", "41146", "1489", "1067"), tags = "task_id")
+)
+
+codomain = ps(
+  mmce = p_dbl(lower = 0, upper = 1, tags = "minimize"),
+  f1 = p_dbl(lower = 0, upper = 1, tags = "maximize"),
+  auc = p_dbl(lower = 0, upper = 1, tags = "maximize"),
+  logloss = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
+  ramtrain = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
+  rammodel = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
+  rampredict = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
+  timetrain = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
+  timepredict = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
+  mec = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
+  ias = p_dbl(lower = 0, upper = Inf, tags = "minimize"),
+  nf = p_dbl(lower = 0, upper = Inf, tags = "minimize")
+)