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Mar 25, 2025
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Update README and web page #88

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1648871
Merge pull request #79 from yuta-nakahara/hotfix-visualize_model_of_b…
yuta-nakahara Oct 31, 2023
aa11ee8
Merge pull request #81 from yuta-nakahara/release-0.2.5
yuta-nakahara Nov 6, 2023
bd15c49
Merge pull request #85 from bayesml/release-0.3.0
yuta-nakahara Mar 9, 2025
69e2542
Update README and web page
yuta-nakahara Mar 21, 2025
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5 changes: 5 additions & 0 deletions README.md
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Expand Up @@ -3,10 +3,15 @@ Document Author
Yuta Nakahara <yuta.nakahara@aoni.waseda.jp>
Shota Saito <shota.s@gunma-u.ac.jp>
-->

---

<div align="center">
<b>Our algorithm for the meta-tree model is accepted at AISTATS 2025! Click <a href="https://bayesml.github.io/BayesML/examples/metatree_prediction_interval.html">here</a>!</b>
</div>

---

<img src="./doc/logos/BayesML_logo.png" width="600">

## Purpose
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5 changes: 5 additions & 0 deletions README_jp.md
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Document Author
Yuta Nakahara <yuta.nakahara@aoni.waseda.jp>
-->

---

<div align="center">
<b>メタツリーモデルに対するアルゴリズムがAISTATS 2025に採択！詳細は<a href="https://bayesml.github.io/BayesML/examples/metatree_prediction_interval.html">こちら</a>！</b>
</div>

---

<img src="./doc/logos/BayesML_logo.png" width="600">

## 目的
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47 changes: 25 additions & 22 deletions doc/examples/metatree_prediction_interval.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"### Installation of BayesML\n",
"\n",
"Installation from PyPI will be available soon. Until then, please follow these steps:\n",
"\n",
"1. Clone BayesML from https://github.com/bayesml/BayesML.\n",
"2. Change the directory and move to the root of the cloned BayesML folder where setup.py exists. (e.g., /Users/UserName/Documents/GitHub/BayesML)\n",
"3. Run `pip install .`"
"### Installation of BayesML"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"!pip install bayesml"
]
},
{
Expand All @@ -29,7 +32,7 @@
},
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"execution_count": 1,
"execution_count": 2,
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{
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"4 -0.002592 -0.031988 -0.046641 135.0 1.0 "
]
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"metadata": {},
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}
Expand All @@ -186,7 +189,7 @@
},
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"outputs": [],
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},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 6,
"metadata": {},
"outputs": [
{
Expand All @@ -303,7 +306,7 @@
"<bayesml.metatree._metatree.LearnModel at 0x14f49d0d0>"
]
},
"execution_count": 5,
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
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{
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"execution_count": 9,
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"metadata": {},
"outputs": [
{
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},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 11,
"metadata": {},
"outputs": [
{
Expand All @@ -478,7 +481,7 @@
"<bayesml.metatree._metatree.GenModel at 0x16b81c610>"
]
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"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
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{
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{
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"execution_count": 13,
"metadata": {},
"outputs": [
{
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47 changes: 25 additions & 22 deletions docs/_sources/examples/metatree_prediction_interval.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -11,13 +11,16 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"### Installation of BayesML\n",
"\n",
"Installation from PyPI will be available soon. Until then, please follow these steps:\n",
"\n",
"1. Clone BayesML from https://github.com/bayesml/BayesML.\n",
"2. Change the directory and move to the root of the cloned BayesML folder where setup.py exists. (e.g., /Users/UserName/Documents/GitHub/BayesML)\n",
"3. Run `pip install .`"
"### Installation of BayesML"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"!pip install bayesml"
]
},
{
Expand All @@ -29,7 +32,7 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 2,
"metadata": {},
"outputs": [
{
Expand Down Expand Up @@ -163,7 +166,7 @@
"4 -0.002592 -0.031988 -0.046641 135.0 1.0 "
]
},
"execution_count": 1,
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -186,7 +189,7 @@
},
{
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"execution_count": 2,
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
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"metadata": {},
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},
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"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -284,7 +287,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 6,
"metadata": {},
"outputs": [
{
Expand All @@ -303,7 +306,7 @@
"<bayesml.metatree._metatree.LearnModel at 0x14f49d0d0>"
]
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"execution_count": 5,
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
Expand Down Expand Up @@ -334,7 +337,7 @@
},
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"execution_count": 7,
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},
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"metadata": {},
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{
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},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 11,
"metadata": {},
"outputs": [
{
Expand All @@ -478,7 +481,7 @@
"<bayesml.metatree._metatree.GenModel at 0x16b81c610>"
]
},
"execution_count": 10,
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
Expand Down Expand Up @@ -509,7 +512,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 12,
"metadata": {},
"outputs": [
{
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},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 13,
"metadata": {},
"outputs": [
{
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