Window Mining

[Mirta Dozar]

Forboth Nvidia and AMD, you can set up parameters: power limit, core clock, memory clock, and static fans. For Nvidia you can also set locked core clock and for AMD you can set up core voltage and memory voltage.

You can use minerstat for Windows on personal computer, but we don't recommend it. We recommend mining on dedicated rigs and computers with a mining-prepared environment which is separated from the personal and sensitive data.

We support mining of all coins for algorithms that are available with listed mining clients. For more than 250 coins and 250 multi-algo pools options we are also providing estimated earnings calculations.

We support mining on all pools - our current database includes more than 2,000 different pools and more than 250 multi-algo pools options, including the most popular ones Ethermine, Nanopool, Mining Pool Hub, NiceHash, zpool, and others.

minerstat isn't just another calculator - it's a powerful mining platform that supports your crypto journey. Boost your profits, save valuable time, and maximize efficiency with our suite of premium features:

I have a broad question about sliding window validation. Specifically, I am looking at using Rapid Miner to predict future values of a financial series using "lagged" values of that series and other covariates. I have been experimenting with the windowing operator in this software and lagging the values to prepare for modeling. What I am confused about, and suspect this is a general process, not just something centric to Rapid Miner and thus I ask it here, is the sliding window training/evaluation process.

Specifically when building a model, I think I understand that k instances are used to train a model (e.g. SVM) and the performance of this model is determined by predicting the next m records. Then, the window is slid forward some amount and the next k records are used for training and the evaluation is done on the subsequent m records. This continues until the end of the data.

Your understanding about sliding window analysis is generally correct. You may find it helpful to separate the model validation process from the actual forecasting. In model validation, you use $k$ instances to train a model that predicts "one step" forward. Make sure each of your $k$ instances uses only information available at that particular time. This can be subtle, because it is easy to accidentally peek ahead into the future and pollute your out-of-sample test.

For example, you might accidentally use the entire time series history in feature selection, and then use those features to test the model at every step of time. This is cheating, and will give you an overestimate of accuracy. This is mentioned in Elements of Statistical Learning, but outside the sliding window time series context.

360mining caters finance, supply chain, HR, stock, asset, OSHE and riskmanagement. Whether operating fixed or mobile plant & equipment, 360Mining has the answer. Should it be serial, or location controlled, from singlecomponent to multi-level component structures such as mining processing plants,excavators and draglines with accessories and attachments.

Extensivebest practice maintenance templates for easy Job Card creation, allowing fortrades, spares, replacements and contractors. Job Card Activities can bespecified in detail steps inclusive document attachments. With comprehensivemaintenance planner for the effective allocation and management of resources,tracking progress, costs (budget vs actual vs industry) and compliance.

In order to find patterns in data, it is often necessary to aggregate or summarise data at a higher level of granularity. Selecting the appropriate granularity is a challenging task and often no principled solutions exist. This problem is particularly relevant in analysis of data with sequential structure. We consider this problem for a specific type of data, namely event sequences. We introduce the problem of finding the best set of window lengths for analysis of event sequences for algorithms with real-valued output. We present suitable criteria for choosing one or multiple window lengths and show that these naturally translate into a computational optimisation problem. We show that the problem is NP-hard in general, but that it can be approximated efficiently and even analytically in certain cases. We give examples of tasks that demonstrate the applicability of the problem and present extensive experiments on both synthetic data and real data from several domains. We find that the method works well in practice, and that the optimal sets of window lengths themselves can provide new insight into the data.

We thank Heikki Mannila for useful discussions and feedback. This work was supported by the the Finnish Doctoral Programme in Computational Sciences (FICS), the Finnish Centre of Excellence for Algorithmic Data Analysis Research (ALGODAN) and the Finnish Centre of Excellence in Computational Inference Research (COIN). We acknowledge the computational resources provided by Aalto Science-IT project.

The selection of an optimal set of window lengths is based on the squared error between predictions made using those window lengths (Problem 1). Under the constraint of using a \(k\)-partition nearest neighbour regressor, the predictions correspond to the value of the nearest window length (Sect. 4.1). Thus, to select the optimal window lengths, we have to compute the distance (squared error) between all pairs of window lengths. We find that the distance between window lengths is as follows.

The install process for using Ubuntu Linux for mining is quite a different story. When trying to choose between Windows or Linux for mining you might be surprised just how much faster Ubuntu Linux installs. On a decent mining machine the install might be as little as 15 minutes, and there is only one reboot required! The install screens are a lot less glamorous however, and some technical questions the average user might not know the answers too.

That being said, Windows 10 has come a long way. With some registry and policy tweaks to stop reboots and put them on your preferred schedule, Windows 10 is far more stable than Windows 8 that came before it.

Ubuntu Linux has won this battle. There is no comparison. I have Ubuntu Linux servers running in mission critical environments with years of uptime. This is because in many cases we can deploy patches to services and applications without a reboot.

Windows and Linux both have decently powerful scripting tools. In Windows you have batch files that are super simple to use, and PowerShell for more advanced users (it takes a while to get good at PowerShell). In Linux you have shell scripting which is similar to batch, along with a host of other scripting tools. Linux is the Swiss army knife in this regard.

Windows also offers some decent scripting languages and of course PowerShell. With PowerShell you can do some really advanced stuff. If your mining rig and your gaming PC are the same computer, PowerShell can pause mining as soon as it sees World of Warcraft running. A pretty sweet feature!

Linux has some cool features and one of them is the Crontab. This file runs on a schedule and can be programmed to check the status of your mining operation every so often and make adjustments. This could be something as simple as making sure your software is still running to actually checking the price of coins and profit switching to a coin that is more profitable at that moment.

The choice is ultimately going to come down to your comfort level. If you know Linux or have used it in the past, then its probably going to be the ideal choice for your mining operation. For newbies or someone just getting into mining, Windows is certainly going to present the least amount of challenges to your new found hobby/business.

Before we go I wanted to introduce another option that has intrigued me recently. Simple Mining OS is a custom port of Linux designed specifically for miners. You have to pay a small monthly fee to use and manage the OS from their centralized web portal, but it does take a lot of guesswork out of the Linux equation for those not interesting managing them. There are specific versions for different video cards and they make it super easy to overclock them and control fans. Might be worth paying someone else to deal with the headaches.

I also have an article on learning how to mine Ethereum, which is my favorite coin to mine using GPUs. If you decide to mine on Windows, you can learn all about overclocking a mining GPU here. Or specifically how to overclock the AMD RX 580 for mining here, which requires a special mining BIOS mod to get the full potential.

I am thinking using LINUX for bitcoin mining. I have a NVIDIA GEFORCE GT710 GPU, and I am thinking of using this old machine to start mining bitcoin. Not sure, there is any graphic driver issues on Linux. Could you someone comment on this? I am a Linux USER, though not an expert.

There have been a number of high-profile reports and incidents that have flagged human rights concerns in mining operations owned by Chinese firms. Researchers at the Business and Human Rights Resource Centre recorded 102 violations of human rights and environmental laws at 39 Chinese mines in 18 countries between January 2021 and December 2022. The Zimbabwe Environmental Law Association has flagged that miners working for Chinese firms receive low wages and go months without wages, and that consequences for speaking out can be fatal.

There is evidence that some African countries are moving away from a mining sector dominated by Chinese firms. There have been significant investments from Australian, Japanese and British, and U.S. mining firms in the region in the last 18 months. It is not too late if the United States is willing to invest in partnerships with African countries. Countries are actively seeking out partnerships with diversified partners, particularly for financing and technical expertise for value chain development, to maximize their benefits from the green energy transition.

3a8082e126